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CHARISMA – D3.3 – v2.0 Page 1 of 43
Converged Heterogeneous Advanced 5G Cloud-RAN Architecture for
Intelligent and Secure Media Access
Project no. 671704
Research and Innovation Action
Co-funded by the Horizon 2020 Framework Programme of the European Union
Call identifier: H2020-ICT-2014-1
Topic: ICT-14-2014 - Advanced 5G Network Infrastructure for the Future Internet
Start date of project: July 1st, 2015
Deliverable D3.3
Initial Content Caching and Traffic Handling at SW
Regex Integration
Due date: 30/06/2016
Submission date: 15/07/2016
Deliverable leader: Yaning Liu
Dissemination Level PU: Public
PP: Restricted to other programme participants (including the Commission Services)
RE: Restricted to a group specified by the consortium (including the Commission Services)
CO: Confidential, only for members of the consortium (including the Commission Services)
Ref. Ares(2016)3477231 - 15/07/2016
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List of Contributors
Participant Short Name Contributor
JCP-Connect JCPC Yaning LIU, Matthias Sander Frigau
Demokritos NCSRD NCSRD Eleni TROUVA, Yanos Angelopoulos
Intracom Telecom ICOM Konstantinos KATSAROS
Fundació i2CAT I2CAT Shuaib SIDDIQUI, Eduard ESCALONA
University of Essex UESSEX Michael PARKER (Internal Reviewer)
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Table of Contents
List of Contributors ................................................................................................................ 2
1. Introduction ...................................................................................................................... 6
1.1. Background ........................................................................................................................................ 6 1.1.1. State-of-the-art .......................................................................................................................... 6 1.1.2. Gap analysis ............................................................................................................................... 8
1.2. Design requirements ........................................................................................................................10
2. CHARISMA Content Delivery System ........................................................................12
2.1. Objectives and System Overview .....................................................................................................12
2.2. CHARISMA distributed caching framework .....................................................................................16 2.2.1. Identification of cache location ...............................................................................................16 2.2.2. Virtualized cache as a VNF .......................................................................................................16 2.2.3. Virtualized cache controller as a VNF ......................................................................................19 2.2.4. VNFD Descriptors .....................................................................................................................21
2.3. CHARISMA traffic handling ..............................................................................................................22 2.3.1. Problem statement ..................................................................................................................22 2.3.2. The CHARISMA approach .........................................................................................................24
2.4. Security issues related to CHARISMA content delivery system ........................................................26
2.5. ICN based content delivery in CHARISMA ........................................................................................27 2.5.1. Latency benefit ........................................................................................................................28 2.5.2. Mobility benefit .......................................................................................................................28
3. Interface design of CHARISMA cache system .........................................................29
3.1. Overview and requirements of interface design ..............................................................................29
3.2. Communication between cache nodes ............................................................................................29
3.3. Interfaces between cache nodes and cache controller ....................................................................31
3.4. Interfaces to VNF manager ..............................................................................................................31
4. Overview of primitive implementation .......................................................................33
4.1. Cache Nodes and Cache Controller ..................................................................................................33
4.2. VNF Descriptor .................................................................................................................................35
5. Conclusions ..................................................................................................................39
References ............................................................................................................................40
Acronyms ..............................................................................................................................42
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List of Figures
Figure 2-1: CHARISMA four converged aggregation levels (CALs) architecture .............................................. 13 Figure 2-2: CHARISMA Caching solution with management ........................................................................... 14 Figure 2-3: Call flows for the management of cache slice and cache/pre-fetch ............................................. 15 Figure 2-4: CHARISMA Cache Node Software Components ............................................................................ 17 Figure 2-5: Content Delivery Procedure Initiated by User Equipment ............................................................ 18 Figure 2-6: Netconf Architecture ..................................................................................................................... 20 Figure 2-7: CHARISMA Content Caching Architecture .................................................................................... 20 Figure 2-8: CHARISMA Prefetching Procedure Controlled by CC .................................................................... 21 Figure 2-9: Delay components in the case of v-Caching ................................................................................. 23 Figure 2-10: CHARISMA solution for cacheable traffic identification and handling (managed by the VNO) .. 26 Figure 3-1: Example operation of vCache peering in multi-tenancy scenarios. A cache miss in the vCache of
VNO 1 results in the redirection of the content request to the vCache instance of the co-located VNO 2. ............................................................................................................................................................. 30
Figure 3-2: CHARISMA solution for cacheable traffic identification and handling (managed by the infrastructure operator).......................................................................................................................... 32
Figure 4-1: The MoBcache prototype .............................................................................................................. 33 Figure 4-2: Diagram of the logical architecture ............................................................................................... 34
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Executive Summary
This deliverable D3.3 “initial Content Caching and Traffic Handling at SW Regex Integration” provides the
initial results arising out of the Task 3.4 “Content Caching and Traffic Handling at the RAN node” in Work
Package 3 during the first year of the CHARISMA project. The purpose of Task 3.4 is to provide a CHARISMA
content delivery service featuring the key CHARISMA performance characteristics of: low latency, open
access and security. This deliverable’s main aim is to describe in detail the design of the CHARISMA content
delivery system that has been developed in T3.4. As part of that design process we have investigated how an
information-centric networking (ICN) approach allows the CHARISMA content delivery solution to benefit
from the low latency and mobility of ICN technology.
We describe how content delivery solutions in current networks operate, with an analysis of the gaps in these
current technology solutions, in terms of their inability to support virtualized caching solutions and caching-
related traffic handling solutions.
The distributed caching locations in the CHARISMA network have been identified with each of the different
Converged Aggregation Levels (CALs) of the CHARISMA architecture. The advanced CHARISMA MoBcache
system has been designed to provide a virtualised and intelligent seamless service in a mobile 5G scenario.
Virtualization of the cache nodes and cache controller allows the dynamic deployment of network caches,
and cache management for CHARISMA subscribers according to their requirements and network status.
Through dynamically allocating virtualized caches and the cache controller to a virtual network operator
(VNO), the CHARISMA content delivery system is also able to provide open access and multi-tenancy services.
Traffic handling has also been investigated in this deliverable, with traffic cacheability and the caching
operation analysed, such that a selective traffic offloading strategy can be deployed in order to improve the
service access time latency.
Security issues related to the content delivery system have also been identified and discussed, but the design
and implementation of solutions for these security issues will be considered as future work in the second
year of the project.
As part of integrating the work of T3.4 with the rest of the work package WP3, the CHARISMA control,
management & orchestration (CMO) system has been interfaced to the CHARISMA content delivery system.
The virtualized caching resources are also to be managed and controlled by the CHARISMA CMO system.
Initial integration of the MoBcache content delivery system with the CHARISMA intermediate low latency
demonstrator has also been achieved, and is described in the parallel deliverable D4.1. On-going integration
of MoBcache into the overall CHARISMA system pilots is a feature of the T3.4 work into the second year of
the CHARISMA project.
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1. Introduction
This document presents the initial design of the CHARISMA content delivery system based on in-network
caching, as well as the traffic handling solutions that will assist in the optimum management of such a caching
system. The definitions of the different components and their associated interfaces forming the CHARISMA
MoBcache are described in this document, as are the interfacing and integration with the CHARISMA control,
management & orchestration (CMO) system. The work presented here represents the output of the first
year’s technical work in the CHARISMA task T3.4 “Content Caching and Traffic Handling at the RAN node” of
work package WP3.
The CHARISMA content delivery system is targeting to support the three main objectives of the CHARISMA
architecture: open access, low latency and security. It has been designed to provide an open accessible,
highly configurable, efficient and transparent in-network caching service to improve the content distribution
efficiency by distributing content across the different hierarchies of the CHARISMA Converged Aggregation
Levels (CALs) in the network. The MoBcache has been designed to be an open cache access solution using
virtualization of the caches and the Cache Controller (CC). This allows the dynamic allocation of virtualised
slicing of caches and the CC to different service providers (SPs) or virtualized network operators (VNOs) over
the same common infrastructure. Furthermore, the security issues related to the caching solutions have been
discussed and will be designed and implemented in the future work.
We note that the SW regular expression (Regex) technique suggested in the title of this deliverable is not
actually discussed in this document, for several reasons: First, in order to meet the three key objectives of
the CHARISMA project (low latency, open access and security), a design of the CHARISMA content delivery
system including the definition of the architecture and the integration to the CHARISMA CMO infrastructure
is required, that goes beyond the SW regex integration of the caching solution. In addition, although regex
matching solutions have been used for Deep Packet Inspection (DPI), the SW regex technique is only one of
various techniques which we can use for our DPI solution for the identification of requested content items;
however, it is not especially optimised for low latency, especially in the vCache context, and so we have
adopted an alternative DPI approach, as described in chapter 2, based on SDN primitives, that targets the
identification of traffic amenable to caching at the TCP/IP flow level.
1.1. Background
1.1.1. State-of-the-art
Internet traffic keeps growing at pace as a consequence of the steadily increasing number of users and the
adoption of new bandwidth-intensive services (such as video services) by end users. According to recent
studies [1], global IP traffic has increased more than fourfold in the past 5 years, and is expected to increase
a further threefold over the next 5 years.
In order to reduce network traffic and improve Quality of Service and Quality of Experience (QoS/QoE) for
end users, caching schemes have been proposed in Content Delivery Networking (CDN). In a CDN
infrastructure, a set of CDN servers is distributed in the network to replicate content and facilitate its delivery
to end-users. Commercial CDNs like Akamai and Limelight have been successfully deployed in the current
Internet. Recent reports [1] show that about one third of Internet traffic was carried by CDNs in 2012, and
by 2017 the traffic crossing CDNs is anticipated to have grown by 51%. Moreover, due to the increasing
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popularity of smart phones and emerging mobile applications, mobile Internet is dramatically expanding. The
Cisco Visual Networking Index (VNI) report [1] shows that Internet traffic from wireless and mobile devices
will exceed traffic from wired devices by 2016 and nearly half of Internet traffic will originate from non-PC
devices by then. Global mobile traffic is anticipated to increase nearly eleven-fold by 2018.
To meet the growing bandwidth demands of mobile users, commercial Long-Term Evolution (LTE) networks
are being deployed to significantly increase the bandwidth and reduce the latency experienced in the mobile
network. Though LTE improves the network performance between end users and the mobile network, the
service latency still highly depends on the distance between the data centre and the exchange point where
the mobile network connects to the Internet. Ensuring low service latency is crucial to satisfying the QoS of
current applications, especially for latency-sensitive applications such as audio and video services. Moreover,
LTE network backhaul bandwidth will be heavily consumed by duplicated data streams when content (such
as high-popular videos) is requested simultaneously and frequently. The authors in [2] analysed the gains of
Hypertext Transfer Protocol (HTTP) content caching at the location of Serving Gateway (SGW) in an LTE
Wireless network, and they found that 73% of the data volume and around 30% of the responses are
cacheable. Mobile network caching could be a cost-effective solution to improve the service latency and
reduce the mobile backhaul traffic by replicating popular and frequently demanded content in Internet
Protocol (IP)-based 3G/LTE network elements closer to mobile users.
Historically, content was stored in centralized locations owned and operated by the original creators of the
content. Caching content closer to the users in a network is an effective way for network operators to offload
traffic from the core segment of the network, where contents are usually stored in data centres. Because of
the tremendous growth of traffic expected in the next few years, various studies [1] and [4], have identified
the risk of traffic bottlenecks in the core network infrastructure that could severely compromise the
performance of services such as Video on Demand (VoD), Online Gaming, File Sharing, Media Streaming, etc.
The deployment of distributed metro/access replicated caches in the aggregated infrastructure allows
decreasing congestion of the core network and ensures fast content delivery in a distributed way. It also
enables a more scalable architecture, since the content is replicated in several locations of metro/access
networks. As VoD and Over the Top (OTT) services increased in volume, network operators began to search
for improved models with the intention of reducing the total load in the network, improving user experience
and maintaining customer satisfaction, as well as providing a mechanism to monetize the delivery of content-
based distribution, perhaps by enabling advert insertion. Operators therefore adopted content cache
support on or collocated with less centralized, Broadband Remote Access Server (BRAS) devices until such
time that a distributed approach was standardized. The Broadband Forum specifications for Digital
Subscriber Line Access Multiplexers (DSLAMs) incorporate cache facilities, including content offload
interfaces, content injection and Deep Packet Inspection (DPI, an enabler of content based functions). Such
tools have supported operator business models and enabled a distributed content distribution model. For
fixed line services, the edge access aggregation point (OLT or G.fast) is the deepest one might want to go
with cache facilities while for mobile services this model could be insufficient. As mobile services traverse
more devices before accessing the packet gateway such as the base station itself, and more than likely, a cell-
site aggregator to which multiple base stations are attached for efficient backhaul, so the latency and Quality
of Experience demands cause operators to anticipate a deeper, more distributed content cache topology.
The in-network caching system can be managed in both proactive and reactive ways. The proactive approach
manages the in-network caching by means of pushing content into the caching devices. This pushing
operation could be particularly useful in live audio/video streaming delivery since it is easy to anticipate the
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users’ request. The pushing method also allows for prefetching of content that a user could potentially
requested onto a cache located in the network at a location that a mobile user will move to. The popularity
of the content and the users’ social behaviour can also be used to improve the accuracy of predicting the
pre-fetched content. On the other hand, on-path caching is applied in a reactive approach. Here, the on-path
caching allows every caching device that forwards the content to temporarily keep the data in its cache.
Software Defined Networking (SDN) has been investigated in a study [5] to provide cache as a service. The
main idea here is to separate the data plane and control plane that orchestrates the caching and distribution
functionalities, and transparently push the content as close as possible to the users. An SDN based in-network
service has several advantages. First, it improves network utilisation and minimises the external link usage
on the last mile that is often costly. Second, it reduces the distribution load for the content service. Third,
through transparent caching enabled closer to the end users, the distance between the content server and
end users is reduced. Furthermore, SDN allows vendor-agnostic deployment of the caching solution on
commodity hardware while providing a centralised network overview, via monitoring, enabling rapid load
balancing which in turn improves QoE of the end users. Another study [19], has investigated content based
traffic engineering techniques based on software-defined Information Centric Networking (ICN). The
content-based traffic engineering and load balancing in the caching solution is supported by a controller
based on SDN principles. All the cache nodes in the network announce their content to the controller, which,
in turn having a global view, performs traffic engineering and load balancing to achieve maximum efficiency.
Network functions virtualization (NFV) (also known as virtual network function (VNF)) offers a new way to
design, deploy and manage networking services. NFV decouples the network functions, such as network
address translation (NAT), firewalling, intrusion detection, and caching, from proprietary hardware
appliances so they can run in software to accelerate service innovation and provisioning. For example, a
virtual Router or vRouter is a software function that represents the functionality of a hardware-based IP
routing. Virtual router is a form of NFV where the functions of hardware-based network appliances are
converted to software that can be run on standard commercial-off-the-shelf (COTS) hardware. In this way,
in-network caching can be presented as software functions and be virtualized as a virtual Cache or vCache.
In a more sophisticated distributed caching environment, pieces of the caching software can be moved
around entire networks while managed with a centralized control plane. In this way, caching functions can
be easily and quickly installed and provisioned in the network, as well as dynamically configured or adapted
to the network needs. With virtualization of in-network caching, network operators can lower the costs for
managing caching services deployed in the network, allow easier scaling of available hardware cache
resources, and be able to achieve security and integrity through separation and isolation.
The two-abovementioned technologies, NFV and SDN, together can enable dynamicity and flexibility for a
caching solution as the former allows flexible provisioning for the caching functions itself whereas the latter
provides the required rapid automatic network provisioning.
1.1.2. Gap analysis
The realization of caching functionality on top of virtualised computing, storage and network resources
presents a series of opportunities for novel features, as well as challenges on how to take advantage of the
elasticity of resources available. In the following we discuss how the current state-of-the-art fails to address
the new emerging challenges, calling for corresponding advances on several fronts.
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The virtualised character of the resources and the corresponding software based realization of the caching
functionality support a flexible model for the dynamic instantiation of cache instances across both time (i.e.,
selecting when to instantiate a cache) and space (i.e., selecting the location to place a cache). As the vast
majority of current caching infrastructure relies on dedicated hardware, the cache placement problem (i.e.,
which network locations caches should be deployed at) has been traditionally addressed as a one-off long-
term decision pertaining to network planning and dimensioning. The current state of the art therefore only
foresees the formulation of problems related to the static placement of the cache locations, subject to long
term observations of the demand, usually in the form of a facility location problem e.g.,[12]. However,
virtualization introduces the aspect of time, decoupling the deployment of a cache instance from any physical
deployment constraints. This opens new challenges in also identifying when a cache is mostly needed in a
certain network, subject to workload dynamics and estimations of latency and traffic savings. The elasticity
of the virtualised resources enables the efficient management of the available resources, allowing (Virtual)
Network Operators ((V)NOs) to utilize the leased resources when there is actually a well-justified need for
this.
The elasticity of the resources further poses challenges related to the auto-scaling of the virtual caching
infrastructure. As the caching workload may vary through time, it is required that the correct amount of
resources is devoted to the caches avoiding cases of overloading or underutilization. Though auto-scaling
approaches have been traditionally based on the instantiation of new Virtual Machines (VMs) in the cloud
environment (scale out), the case of caching functionality presents important specificities. Namely, the scale
out operation of virtualized caches is expected to lead to new VM instances with non-initialized caching state,
since caches typically require a warm up period to gradually store the most popular content. The instantiation
of new VM images bears therefore the risk of not reaping the benefits of scaling out immediately i.e., the
required warm up period is expected to result in the reduced efficiency of the newly spawned cache instance.
Though a potential solution can be based on the use of VM snapshots (i.e., a copy of an existing VM is
instantiated, including the current state), this is expected to lead to the non-efficient utilization of the
allocated resources: two identical virtual caches are expected to share the expected load for the common
most popular content items, but at the same time consume duplicate resources for the same content e.g.,
duplicate copies of the same least popular content. Therefore, a right balance between popular and non-
popular content, as well as the right cache content diversity across virtual cache instances is required.
On another front, given the flexible control of the overall virtual topology, a new opportunity arises regarding
the handling of traffic in the context of virtual caching, with a particular focus on achieving low delays. This
opportunity stems from the observations that not all traffic can benefit from caching (e.g., conference calls),
and that steering traffic through a cache results in delay overheads related to the protocol stack traversal
and the cache index lookup operation. While such delays are acceptable in the case of a cache hit, where the
latency to retrieve the content from its origin is avoided, the same does not hold for a cache miss, since in
this case, latency increases as compared to the case of not employing a cache. An important challenge then
relates to the identification of the traffic amenable to caching and the corresponding steering of the traffic
through the cache or not i.e., bypassing caches when necessary. Recently proposed approaches aim at
maintaining up-to-date state for the content currently cached in the available virtual caches (vCaches),
supporting thus an explicit lookup of all requested items before taking a forwarding decision i.e., each
content item requested is looked up in a (logically) centralized repository in order to locate (or not) the cache
location(s) that hold(s) a copy and subsequently forward the request accordingly [13]. This approach is
considered as inherently tight to large overheads related to (i) the required deep packet inspection (DPI)
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functionality for the identification of the requested content item, and (ii) the maintenance of up-to-date state
for all the content in the vCaches i.e., cached content may have limited lifetime within the cache, calling for
a frequent updating of the state maintained in the aforementioned (logically) centralized repository; also the
volume of information for this mechanism may be considerably high, especially for multiple cache locations
of large capacity. Later in this document we discuss an alternative approach, which based on SDN primitives,
targets the identification of traffic amenable to caching on a TCP/IP flow level.
Finally, considering caching in the context of multi-tenancy scenarios opens up opportunities for new models
of co-operative caching and business relationships between Virtual Network Operators (VNOs). As the same
physical infrastructure can support multiple tenants, it is possible that virtual cache instances belonging to
different VNOs are physically collocated on top of the same hardware. Since the communication between
such closely located instances is expected to present significantly low latencies - a major objective for
CHARISMA - a new model of VNO inter-domain relationship emerges, foreseeing the peering of virtual caches.
In this model, caches of different VNOs are configured to act as siblings in a co-operative caching scheme.
Such an approach is expected to yield mutual benefits for VNOs, which may in this manner avoid excessive
traffic across the physical network infrastructure. Note that the dedicated use of physical realizations of
caches in the current network model presents no such opportunity, with the exception of co-location of
operators at Internet Exchange Points, which is however based again on dedicated hardware in isolated
cache installations. The interconnection of content distribution networks (CDNi) IETF working group1 has
identified similar objectives, by foreseeing the interconnection of cache instances of different CDNs. However,
the related approaches focus on mechanisms explicitly tailored for the interconnection of overlay CDNs, and
as such they do not provide experience and technical solutions in the context of the network functions
virtualization (NFV) paradigm adopted by CHARISMA.
1.2. Design requirements The design of CHARISMA content delivery system should meet the three key drivers (low latency, security
and open access) targeted by CHARISMA.
It is a challenge to provide continuous service with low latency in a mobile scenario where user equipment
switches from different wireless/mobile networks. For example, in the automotive – bus use case presented
in Section 4.2.3 of CHARISMA’s Deliverable D1.1, some intelligence like caching, switching and routing closer
to end users has been defined to assist in reducing network latency. However, providing intelligence in a
wireless / mobile scenario requires a sophisticated design for the hardware device. Hence, two kinds of cache
nodes need are being designed and implemented in CHARISMA: a dedicated cache box called MoBcache and
virtualized caches (vCaches). MoBcache is specially designed for mobile scenarios in the CHARISMA system
with two Wi-Fi interfaces (802.11n and 802.11ac) and one LTE dongle, in order to keep service continuity
while a user moves about and hand-overs are made between networks. The vCache will be deployed as a
Virtual Network Function (VNF) in the different CHARISMA Converged Aggregation Levels (CALs) and will be
managed by the SDN-based CHARISMA management system. In this way, caching functions can be easily and
quickly installed and provisioned in the network, as well as dynamically configured or adapted to the network
needs.
In order to meet the requirements of the CHARISMA open access approach, the CHARISMA content delivery
system implements virtualization of cache nodes and cache controller to enable the deployment of in-
1 https://datatracker.ietf.org/wg/cdni/charter/
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network caching as software functions running directly over the network commodity hardware. The system
allows virtualised slicing of in-network cache resources to different service providers (SPs) over the same
common infrastructure. Furthermore, the CHARISMA content delivery system is able to allocate virtual slices
on top of the physical infrastructure to different network operators (i.e., not just service providers) and lease
the remote application programming interfaces (APIs) to offer access to the virtualised network resources.
Finally, security issues related to the deployment of content caching in the network need to be considered
in the CHARISMA content delivery system. The security requirements considered by the CHARISMA system
include:
o Content Access Trackability: content providers are more and more interested in tracking every access to
their content (i.e., YouTube, Netflix) to avoid copyright problems or legal issues.
o Content Confidentiality: we must enforce content confidentiality for authorized users.
o Access Privilege Violation: an end-user can still retrieve a popular content even if its access privilege to
this content has been revoked. Content origin server will not be aware of this access violation.
o Cache Monitoring Attacks: a malicious user can monitor the behaviour of other users in the same local
cache (e.g., DSLAM, home gateway). Implementing smart caching policies can prevent this.
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2. CHARISMA Content Delivery System
2.1. Objectives and System Overview This document aims at providing a CHARISMA content delivery system to meet the key drivers in the
CHARISMA project, which include: low latency, open access and security. The CHARISMA content delivery
system is designed to provide an open accessible, highly configurable, efficient and transparent in-network
caching service to improve the content distribution efficiency by distributing the content in the different part
of the network. In the CHARISMA vision, we do not plan to support caching ofall kinds of Internet traffic;
rather we are only focusing on the HTTP content caching solution. HTTP traffic is used by the CHARISMA
content delivery system to show as a set of proofs of concept, including latency, virtualisation and security
achieved by deploying caches in different levels of the network. One potential issue is that the amount of
HTTPS traffic used by some popular websites such as Facebook and YouTube is currently increasing.
Measurements show that, approximately 35% of the total HTTP traffic is HTTPS [2]. In CHARISMA, we assume
this issue can be resolved through agreements between network operators and OTT (or content providers),
which will provide network operators the necessary control over content delivery. This issue could lead to a
standardisation initiative. Today the interface between network related header fields and content related
packet parts is blurred. Ideally packet header fields that are related to network functions such as routing
should be open and set correctly by the originator of a packet. But sometimes these fields are not interpreted
or even deleted by the operators. A typical example is the QoS-relevant Differentiated Service Code Point
(DSCP) field in the IP header: some operators ignore this field, and others even clear it. Complex DPI
algorithms are put in place to guess the wish of the user, although it could be explicitly stated in appropriate
header fields. Instead, a user indication to declare a stream eligible for caching would simplify the task of the
network.
Table 1: Qualitative effect of distance on throughput and download time
Distance
(Server to User)
Network
RTT
Typical Packet
loss Throughput
4GB DVD
Download Time
Local
< 160 km 1.6 ms 0.6%
44 Mbps
(high quality HDTV) 12 min
Regional
(800 – 1600 km) 16 ms 0.7%
4 Mbps
(basic HDTV) 2.2 hrs
Cross-continent
(5000 km) 48 ms 1.0%
1 Mbps
(SDTV) 8.2 hrs
Multi-continent
(10000 km) 96 ms 1.4%
0.4 Mbps
(poor) 20hrs
CDNs can improve the QoS of content delivery services because they deliver content from a location near to
the end consumers of the content. Table 1 illustrates the impact of deploying CDN content servers in different
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locations in the network on throughput and network round-trip time (RTT) [6]. It is obvious that the RTT and
throughput are improved if content servers are deployed close to the end users.
We use the transparent caching approach in our CHARISMA content caching system. Transparent caching is
quite different from most traditional content caching solutions that are usually managed by CDN providers
like Akamai or Google other than the network operators. In traditional CDN solutions, the network operator
has little or no control over the cache servers, and as a result has little visibility into the actual productivity
of those servers or what is being delivered from them. Transparent caching transparently picks up the
appropriate packets and cache requests, so that clients do not need to configure their user equipment to
access the cache. Through deploying transparent caching inside the network, network operators are able to
address a broader range of Internet content. With the knowledge of the network status and the full control
of the network, transparent caching deployed by network operators can make better decisions about which
content can and should be cached locally to optimize the network. By deploying intelligent caches
strategically throughout their networks, operators can cache and deliver popular content close to subscribers,
thus reducing the amount of transit traffic across their networks. Popular content can be delivered very close
to the edge, and content of decreasing popularity can be cached further back in the network, forming a
hierarchical structure.
In the CHARISMA content system, caches will be deployed at the four levels of the converged aggregation
levels (CALs) as defined in CHARISMA deliverable D1.1 and shown in Figure 2-1. A Cache Controller (CC) is
designed to manage and configure cache nodes distributed in the network. The basic function of the CC is to
split the management of content flow and placement from the management of content delivery
infrastructures (e.g., forwarding and caching equipment). Through a collaborative caching solution among
caches in the four aggregation levels managed by the cache controller, CHARISMA caching system can
achieve an optimized caching solution and provide better QoE for end users with both low latency and high
throughput.
Figure 2-1: CHARISMA four converged aggregation levels (CALs) architecture
The CHARISMA project is also targeting to provision of an open cache access solution by virtualization of
caches and CC. The specialist hardware (MoBcache or Ubuntu based cache nodes) with instances of virtual
CHARISMA – D3.3 – v2.0 Page 14 of 43
services is provided on cache nodes in the network. This allows the dynamic allocation of virtualised slicing
of caches and CC to different service providers (SPs) or Virtualized Network Operators (VNOs) over the same
common infrastructure. Figure 2-2 shows the necessary components (in yellow) of the CHARISMA
architecture required to realize the CHARISMA content delivery system.
Figure 2-2: CHARISMA Caching solution with management
These components include:
• vCache, vCC as a VNF, web manager as a Element Management (EM) which will be created for a
specific VNO;
• vCC interfacing to Service Monitoring and Analytics (M&A) to collect required monitoring data for a
specific VNO;
• Cache system interfacing to VNF manager which will interface with the orchestrator;
• Service Policy Manager running as a policy manager in the service policy manager;
• Service Policy Manager interfaces to Service M&A:
• Caching related requirements to Service M&A;
• User location, throughput, RTT, packet loss, etc. ;
• Service M&A has interfaces to VNOs for collecting required monitoring data.
In the control plane of our CHARISMA caching system, there are mainly two kinds of control: one is the slice
management for different VNOs operated by the VNF manager and orchestrated by the Service Orchestrator;
and the other one is cache/pre-fetch management controlled by vCC for a specific VNO as shown in Figure
2-2. In slice management, each VNO is assigned by a cache slice including one vCC and several affected
vCaches located in different parts of the network with required resources like network bandwidth, CPU,
CHARISMA – D3.3 – v2.0 Page 15 of 43
memory and hard-disk storage. In cache/pre-fetch management, CHARISMA content delivery systems allows
VNOs to configure, deploy and manage their own network slide by vCC, without intervention from the whole
CHARISMA platform. With the cache slice configuration provided by the CHARISMA content delivery system,
each of the use cases can be configured with a different configuration of requirements and parameters in
network devices by requiring its own cache slice.
Figure 2-3 presents the procedures of cache slice management and cache/pre-fetch management. When the
CHARISMA content delivery system receives from a VNO a demand for a cache service that is presented by a
cache slice, the Cache Policy Manager first needs to communicate with the Service M&A to verify if the
affected network elements can support both the new and legacy functionalities. Based on the VNO
requirement and the current resource status, the Cache Policy Manager can make an optimised decision,
based on where to add vCaches, and how many resources are to be allocated to each of the vCaches, etc. In
this way, the cache slice can be initiated for the VNO. During the cache slices running time, the Cache Policy
Manager is also responsible for reconfiguring the slices with a global view of network status while still
matching the requirements of the VNOs.
As described before, each VNO is assigned by a vCC that is used to allow this VNO configuring and managing
the assigned resources by its own. The interface between vCC and Service M&A is enabled to allow the VNO
to manage its own slice and perform caching/prefetching operations with sophisticated designed strategies.
Figure 2-3: Call flows for the management of cache slice and cache/pre-fetch
CHARISMA – D3.3 – v2.0 Page 16 of 43
2.2. CHARISMA distributed caching framework
2.2.1. Identification of cache location
In this section we focus on the feasibility and potential methods for an efficient caching solution in access
and aggregation networks. We define a set of key network elements enabling cache functionality in the
networks. Figure 2-1 depicts a scenario where storage and caching functions are enabled in: customer
premises network (Home GateWay (HGW) or Customer-premises equipment (CPE)) in CAL0; mobile access
network (micro base station or small cell,) in CAL1; mobile access network (Advanced Remote Node (ARN),
or eNodeB) in CAL2; and backhaul network (data centres) in CAL3. By caching in the access network and the
collaborative caching among this equipment, content can be intelligently duplicated closer to the mobile
users, and efficiently delivered to/from different parts of the network.
Caching on Home / Residential Gateways
Today’s dominating technique for delivering Internet to the home is based on copper access technologies,
Fibre to the Home (FTTH) or Fibre to the Building (FTTB). A converged residence gateway integrating
DSL/GPON/Ethernet, Wi- Fi and 3G/LTE (such as femtocell, nanocell, etc.) has been designed to provide a
unified service and reduce the mobile backhaul traffic. Several advantages can be achieved by this converged
gateway. First, a mobile device accessing to a Wi-Fi Access Point (AP) does not have services like SMS,
telephone and mobility. Second, femtocells can well support these services; however, the data are normally
tunnelled between the Internet and mobile network, which still consumes a lot of bandwidth in the mobile
network, and probably deteriorates the user experience. In-network caching can be further enabled in a
converged residential gateway to improve network performance, especially when the residential gateway is
located in a public place or at enterprises.
Caching on eNodeB, Macrocell / Cell-Site Gateways
As previously indicated, content cache topologies for mobile services are anticipated to be deeper and more
distributed than has been observed in fixed line residential services. In a mobile network, the first location
where a content cache could be placed would be at the base station itself.
Caching in the Data Centre in the CO
The content distribution servers controlled by the network operator can be also deployed in the Central
Office (CO). The measurement for the access network in FTTH access [7] with 30,000 customers and in an
xDSL network [8] shows that almost 50% of the requests are cacheable and that traffic could be reduced by
one third. A collaborative caching algorithm can further improve the benefit. According to the study of the
interaction of a telco-CDN (ISP regional CDN) [9], an additional 12% to 20% of global traffic can be reduced if
we use collaborative CDN caches located in different COs.
2.2.2. Virtualized cache as a VNF
The CHARISMA Cache Nodes (CNs) are responsible for caching the appropriate HTTP content and delivering
it to end users that have requested it.
CHARISMA – D3.3 – v2.0 Page 17 of 43
Figure 2-4: CHARISMA Cache Node Software Components
Each CN includes several software components shown in Figure 2-4:
Local caching Management Primitive (LMP) manages the caching/prefetching behaviour of local
cache node.
NetConf Server (NCS) allows managing the configuration of LMP based on Network Configuration
Protocol (NETCONF) protocol that is used to manage and configure network devices.
The LMP component is further divided into two components: Cache Proxy (CP) and Pre-Fetch Proxy (PFP),
one for reactive caching and the other for prefetching (proactive caching).
Reactive (or opportunistic) caching is a technique that stores recently delivered content so that it can
be quickly accessed at a later time. The cached content should have already been explicitly requested
by some user, otherwise, it would never be stored in the location.
Prefetching (proactive caching) is a technique that retrieves and stores content in a location in the
network according to the requests of OTT service providers. Therefore, the content is pre-fetched to
the in-network caching device without receiving a prior request for it.
The basic caching procedure provided by CHARISMA content delivery system is illustrated in Figure 2-5. We
assume that Cache Node 1, Cache Node 2 and Cache Node 3 are located in CAL0, CAL1 and CAL2 respectively.
While an end user (UE) sends a content request, the nearest cache node Cache Node 1 behaving as a proxy
will check if the content is cached on itself. Cache Node 1 gets a Cache Miss and talks to other cache nodes
distributed in the network. If the requested content is not cached in the CHARISMA caching system, Cache
Node 1 will send the content request to the original content server to retrieve this content, and then send to
the UE. If the requested content is available in Cache Node 2 in CAL1, Cache Node 1 will retrieve this content
from Cache Node 2 and forward it to UE. Since the distance (network distance or latency distance) between
CAL0 and CAL1 is quite short, the UE is able to get the first content with a lower latency.
CHARISMA – D3.3 – v2.0 Page 18 of 43
Figure 2-5: Content Delivery Procedure Initiated by User Equipment
The NCS is integrated in the CHARISMA CNs in order to support managing caches (including enable/disable
the cache nodes, and configure cache size, cache algorithm, etc.) distributed in the network through a
standard network management and configuration protocol. The NETCONF protocol uses a remote procedure
call (RPC) paradigm. Between NETCONF client and server, the contents of both the request and the response
are fully described in XML DTDs or XML schemas. A client encodes an RPC in XML and sends it to a server
using a secure, connection-oriented session.
To control the behaviour of the CP, the NCS modifies the configurations in the file, and restarts the CP each
time the configuration is changed. We use the Netopeer tool as the implementation of the NCS. Therefore,
the installation of NCS is in fact the installation of Netopeer. The configurations take place through the
TransAPI interface, whose broader role is to allow the NCS to change the settings of various devices (e.g.,
network interfaces), the system (e.g., time zone) and the configuration of caching program on the machine.
The Netopeer tool provides two transAPIs for network interfaces and system configuration. They can be
found in the repository “netopeer/transAPI”. To configure software programs or other devices, customized
transAPIs need to be developed. Fortunately, libnetconf offer the lnctool that facilitates the development of
transAPI by generating the source code, and the Makefile based on the Yang model that is a data modelling
language can be used to model both configuration data as well as state data of network elements.
CHARISMA – D3.3 – v2.0 Page 19 of 43
The overall creation and deployment of caches as VNFs goes through the creation, configuration and
instantiation of the corresponding VMs, as well as the configuration of the network enables the transparent
operation of the cache in the network.
The overall realization of the CN functionality is based on software components installed and deployed on
top of the two distributions of the Linux operating system (Ubuntu 14.05 and OpenWrt chaos calmer 15.05).
The described CN architecture (see Figure 2-4) has been implemented and tested on CHARISMA partner JCP-
Connect’s cache nodes, in which the described protocol stack is installed on top of commercial off-the-self
(COTS) hardware. The realization of a CN within a virtual machine (VM) is therefore straightforward.
The configuration of the network for the support of cache VNFs, includes the configuration of the underlying
switching elements of the VI so as to deliver traffic to the virtual CNs. This corresponds to simple flow rules
applied on the switches by the network (SDN) controller of the architecture. This is accomplished during the
deployment of the overall service and handled by the VIM.
Next, the delivery of the traffic to the CP/PFP components of the CN is based on the appropriate inspection
of the corresponding flow characteristics. In a simple approach, all traffic is delivered to the CN VM, which is
configured to inspect the destination port of incoming flows. This is accomplished by the appropriate
configuration of the VM operating system, e.g., configuration of iptables2. Such a configuration is handled by
the Element Manager of the corresponding VNF. Flows targeting port 80 are delivered to the CP/PFP
components. All other flows are configured to be further forwarded towards their original destination. In an
alternative approach, inspection of incoming flows takes place in the (v)switching fabric, so as to alleviate
the CN VM from the associated overheads. This is considered as especially important for high traffic loads.
For instance, a vSwitch can be instantiated as a separate VNF, allowing the provisioning of the required
resources for the inspection of the incoming flows.
2.2.3. Virtualized cache controller as a VNF
2.2.3.1.The description of cache controller
The objective for the design and implementation of the cache controller is to allow VNO providers to manage
the distribution of content in the caching system (vCaches assigned to them). The cache control and
management operated by the CHARISMA Cache Controller (CC) is based on the NETCONF protocol. NETCONF,
as shown in Figure 2-6, provides mechanisms to install, update, and delete the configuration of network
devices, such as routers, switches, and firewalls. It uses Extensible Markup Language (XML)-based or
JavaScript Object Notation (JSON) data encoding for the configuration data and as the protocol messages.
The NETCONF protocol operations are realized as remote procedure calls (RPCs).
2 https://en.wikipedia.org/wiki/Iptables
CHARISMA – D3.3 – v2.0 Page 20 of 43
Figure 2-6: Netconf Architecture
Netopeer is a set of NETCONF tools built on the libnetconf library. It allows operators and developers to
connect to their NETCONF-enabled devices and control their devices via NETCONF. In our cache system, the
Netopeer client runs on the CC, and the netopeer server runs on each CN.
Figure 2-7: CHARISMA Content Caching Architecture
CC is designed to manage and configure all the CNs distributed in the network. The components mainly
include:
Netconf client implemented by netopeer-cli to allow CC managing CN by Netconf protocol;
CCD daemon is responsible for communicating with Netconf and external modules in an automatic
way. CCD is able to configure the CN and send controlling messages to LMP automatically;
DB stores the full information of CNs, user requested content and the content cached in LMP on
each CN.
CHARISMA – D3.3 – v2.0 Page 21 of 43
Figure 2-8: CHARISMA Prefetching Procedure Controlled by CC
Figure 2-8 shows the CHARISMA prefetching procedure controlled by the CC and initiated by the OTTs or
content providers who have the motivation to optimize the content delivery by caching solutions. When a
content provider receives many requests for the same content from many different users in the same area,
it can also decide to activate content caching for this specific content. The content provider sends their
requirements to the CC based on the agreement between the OTTs and network operators. According to the
information relative to user location and network performance, the CC makes an optimised caching decision
to ask the CNs to prefetch the content requested by OTTs.
Similarly to CNs, the CC has been realized on top of the Ubuntu 14.05 Linux distribution, installed on COTS
hardware. As a result, the realization of a CC as a VM is straightforward.
2.2.4. VNFD Descriptors
As defined in [20], a VNF Descriptor (VNFD) is “a deployment template which describes a VNF in terms of
deployment and operational behaviour requirements”. As the VNFs participate in the networking path, the
VNFD also contains information on connectivity, interfaces and KPIs requirements. The latter is critical for
the correct deployment of the VNF, as it is used by the NFVO to establish appropriate Virtual Links within the
NFV Infrastructure (NFVI) between VNF Component (VNFC) instances, or between a VNF instance and the
endpoint interface to other Network Functions. This section attempts a specification of the VNFDs that we
will use for the implementation of the cache node and cache controller VNFs. The described VNFD has been
defined and is currently used by the T-NOVA project [21].
Assuming a VNFD for a VNF that is composed of more than one VDUs, the VNFD contains the following
segments:
CHARISMA – D3.3 – v2.0 Page 22 of 43
VNFD preamble: The VNFD preamble provides the necessary information for the release, id, creation,
provider etc.
Virtual Deployment Unit (VDU) segment: The VDU VNFD segment provides information about the
required resources that will be utilised in order to instantiate the VNFC. The configuration of this part
may be extremely detailed and complex, depending on the platform specific options that are
provided by the developer. However, it should be noted that the more specific are the requirements
stated here, the less portable the VNF might be, depending on the NFV Orchestrator (NFVO) policies
and the service-level agreement (SLA) specifications. It is assumed that each VDU describes
effectively the resources required for the virtualisation of one VNFC. Fields within the VDU VNFD
segment include:
i) IT resources and platform related information;
ii) The internal structure of the VNF and the connection points of the VDU (name id, type) and the
virtual links where they are connected;
iii) Monitoring parameters to be collected by this VNF, including system related information and
VNF specific metrics;
iv) Scaling parameters defining the thresholds for scaling in-out.
VNF lifecycle events segment: This section of VNFD is related to lifecycle events, where the
technology used for interfacing with the VNF is defined, as well as the appropriate commands
allocated to each lifecycle event.
2.3. CHARISMA traffic handling
2.3.1. Problem statement
Caching in CHARISMA is seen as a means to reduce latency by serving the requested content from locally
stored copies3. However, a careful look at the operation of caches reveals the potential introduction of
additional delay components in the end-to-end communication of end hosts. Such delays first stem from the
need of the user (HTTP) requests to reach the vCache instance in order for a lookup to be performed on the
respective cache index and a potential cached copy of the requested content item to be retrieved. As
vCaching in CHARISMA is primarily considered on the application level4 (i.e., HTTP caching), request packets
are required to traverse the entire protocol stack to reach the application level cache instance (we denote
the associated overhead as tstack). In the particular CHARISMA context of virtualised resources, this traversal
also includes the hypervisor level, i.e., packets need to pass from the hypervisor to the guest operating
system of the VM supporting the vCache (VNF) where the protocol stack traversal takes place. Once request
packets reach the cache on the application level, an additional delay is imposed for the lookup operation (we
denote the associated overhead as tcache). Figure 2-9 schematically shows the described constituent delay
components. User equipment (UEs) send their content (HTTP) requests towards the content provider. An
Intelligent Management Unit (IMU)/micro-Data Center (μDC) hosting a vCache can be reached through a
switching device. We assume that a ta delay overhead is associated with reaching the vCache network
3 Additional benefits include the reduction of workload at the origin server and the overall reduction of traffic within the network. 4 See Section 2.1 for a discussion on an alternative approach.
CHARISMA – D3.3 – v2.0 Page 23 of 43
location. A corresponding tb delay overhead is considered between the IMU and the Content provider. In
general, we assume that:
tstack < ta, and tstack << tb
tcache < ta, and tcache << tb
For simplicity, we consider that these delay overheads remain the same in both communication directions,
e.g., the stack traversal delay overhead of an HTTP request is considered to be equivalent to the stack
traversal delay overhead of the corresponding HTTP response. A more detailed assessment of these delays
will be conducted in our future work.
Figure 2-9: Delay components in the case of v-Caching
We consider the following cases with respect to the lifecycle of a content (HTTP) request:
Cache hit
In this case, a request is directed to the vCache where a cached copy of the requested content is found and
subsequently delivered back to the User Equipment (UE). The content provider is not contacted. While the
tcache and tstack delay overheads are suffered, a cache hit avoids tb.
Cache miss
In this case, the request is directed to the vCache where a cached copy of the requested content is not found
and the request is subsequently delivered to the content provider who returns the content back to the UE.
In this case, all delay overheads suffer, namely: tcache, tstack and tb (ta is suffered in all considered cases).
Cache bypass
In this case, the request is not delivered to the vCache but rather delivered directly to the content provider.
In this scenario, the tcache and tstack delay overheads are avoided while the tb overhead suffers.
Given the above, we next make the following important observations:
CHARISMA – D3.3 – v2.0 Page 24 of 43
Not all traffic is amenable to caching.
The above assessment relies on the implicit assumption that the user traffic (or else, the UE flow)
corresponds to an HTTP request for content that can be cached. However, not all UE flows
correspond to HTTP requests, as is the case, for instance, for flows in a Skype session, and not all
HTTP requests are about cacheable content, i.e., frequently changing content marked by content
providers as non-cacheable. Obviously, forwarding such traffic to an HTTP-level vCache will result in
effectively the same results as a cache miss, i.e., paying the tcache and tstack delay overheads. At the
same time, the use of HTTPS results in encrypted communication resulting in non-identifiable and
hence non-cacheable content. A potential solution for these cases would be to rely on a Deep Packet
Inspection (DPI) component responsible for identifying flows carrying cacheable HTTP traffic.
However, such an approach would also result in the associated delay overheads for the DPI
functionality, as well as for the requirement for the allocation of additional resources for this
operation.
Not all content can be cached.
Though the cost of storage resources has been constantly decreasing, still, storage resources are
finite and do not necessarily allow the caching of all the potentially requested content in the network.
As a result, a cache replacement policy is traditionally employed to select the content to keep cached,
trying to identify content items of the highest popularity5.
2.3.2. The CHARISMA approach
In view of the above observations, CHARISMA’s objective is to reduce the amount of unnecessary delay
overheads suffered in cache misses, by trying to identify the UE flows that are more likely to lead to an actual
cache hit. Equivalently, this pertains to the identification of the UE flows for applications not amenable to
caching (e.g., conference call), as well as UE flows for applications amenable to caching, but with a high
likelihood of a cache miss. The objective then is to steer all identified flows to the available vCache(s), while
bypassing the vCache for the remainder of the UE flows, so as to avoid the aforementioned overheads. Our
approach aims at achieving this identification at the flow level, by identifying destination IP ranges that
correspond to the delivery of content that is amenable to caching. Choosing this identification at the flow
level serves the following purposes:
We avoid the overheads of keeping track what content is actually cached in the available vCaches,
and observing what content is requested, before forwarding to the vCache (or not) takes place.
Though such approaches have been proposed in the past [14], we consider them as inherently having
large overheads related to both the required DPI functionality, for the identification of the content
items requested by UEs, and the maintenance of the up-to-date state by keeping track of all content
cached throughout the network.
By identifying flows, we can define and apply corresponding forwarding rules towards the vCache or
directly towards the content provider.
The solution envisioned by CHARISMA is based on the gradual identification of flows amenable to caching6
based on the close monitoring of the deployed vCache(s) and the subsequent handling of the flows on the
5 Additional criteria have been identified in literature [12], which are beyond the scope of this work. 6 Also termed as “cacheable flows”.
CHARISMA – D3.3 – v2.0 Page 25 of 43
switching/routing level. Figure 2-10 provides a high level illustration of the solution, based on the CHARISMA
generic vCache architecture. Initially all traffic is forwarded through the deployed vCaches. The Element
Managers (EMs) of the instantiated vCaches inspect the cached content and access logs, and derive
information about the destination IPs for both cache hits and cache misses7. For instance, in the case of a
Squid8 web cache, the native access logs report the Uniform Resource Locators (URLs) of the cached content
(which can be resolved to the corresponding IP addresses via DNS), as well as the destination IP addresses of
a cache miss, which correspond to the IP addresses of the content providers, when no
hierarchical/cooperative caching is in place. The collected information from all Element Management (EM)
instances across the network (e.g., the slice of a VNO) is periodically passed to the vCC, which consolidates
the received IP destination addressed in continuous IP address ranges.
The collected destination IP address ranges are subsequently communicated to the available SDN controller,
which is responsible for setting the corresponding rules in the underlying switching/forwarding infrastructure.
The SDN controller may be under the operational control of the infrastructure operator or (as shown in Figure
2-10) realized as a separate VNF so as to be under the direct control of the VNO9. For IP ranges related to
cached content, the SDN controller applies flow rules that instruct the underlying physical or virtual
switching/forwarding infrastructure to forward the respective flows (i.e., the flows targeting these ranges)
towards the vCache. As the identified IP ranges and corresponding rules may reach high volumes, VNOs may
rely on virtualized switches so as to support the scalable operation of this scheme as shown in Figure 2-10.
The whole procedure is subject to a continuous update cycle so as to identify changes in the classified IP
destinations and correspondingly adapt the established rules, e.g. the content delivered from a remote
destination IP is no longer cacheable.
By applying the identified forwarding rules, the VNO also enables the detailed monitoring of the
corresponding traffic i.e., since OpenFlow v1.3, a packet counter can be associated to each rule, enabling the
fine grained assessment of traffic towards promising destinations, i.e. destinations which have been
associated with cacheable traffic. Such information can be subsequently used across a VNO slice for the
selection of network locations for the placement of vCaches. Namely, a VNO can identify the locations where
UEs tend to target providers of cacheable content, thus providing a hint of where (and also when) the
instantiation of a vCache could prove beneficial.
7 Note that within a vCache instance, a cache miss corresponds to cacheable traffic but denotes that the specific item was not cached at the time of the request. 8 www.squid-cache.org/ 9 In the latter case, the VNO has complete control of the overall functionality, limiting the exposure of related monitoring information (traffic and content access) to the infrastructure operator. An alternative model is presented in Section 3.4, where the infrastructure operator manages the envisioned functionality.
CHARISMA – D3.3 – v2.0 Page 26 of 43
Figure 2-10: CHARISMA solution for cacheable traffic identification and handling (managed by the VNO)
2.4. Security issues related to CHARISMA content delivery system CHARISMA provides intrinsically in-network content caching through the use of ICN-based content delivery
networks. Thus, content can be replicated throughout the network. Content can be cached in any arbitrary
location and digitally signed to guarantee its authenticity and integrity. The ICN paradigm comes with many
benefits such as a reduced delivery delay and network congestion thanks to content caching, which greatly
improves the scalability and efficiency of content delivery. It also provides a simpler device configuration and
security at the data level: the lack of source and destination addresses enforces privacy, and caching protects
the content provider from excessive load and more particularly from application-level DoS attacks [17].
Moreover, as the content is provided closer to the end user, traffic is decreased, which reduces the
information to be used by an attacker. While these advantages are particularly attractive for the CHARISMA
content delivery system, ICN-based solutions also introduce many open privacy and security challenges. For
instance, publicly available content is not encrypted and can be inspected by any intermediate router
between the user and the content provider. In addition, ICN suffers from a lack of centralization for
authentication, content access feedback and security, making it more difficult for network administrators to
improve services they provide to end-users. Another concern in in-network caching is that it is hard to avoid
the propagation of illegal and fake content (content with valid names but invalid signatures). Signature
verification countermeasures have been proposed but they require verifying the content signature at each
intermediate router, which is not scalable due to the cost of cryptographic operations.
The security requirements considered by the CHARISMA system can be summarized as follows:
Content Privacy & Confidentiality
As shown during the Netflix Prize Contest, the video rental history of an individual can potentially reveal
CHARISMA – D3.3 – v2.0 Page 27 of 43
sensitive personal information, thus, it is of paramount importance to enforce content confidentiality for
authorized users.
While traditional IP-based solution such as secure tunneling (SSL, TLS) can still be a viable approach, it tends
to weaken the cache capabilities, increasing network load and latency.
In CHARISMA, we envision confidentiality and privacy enforcement by the means of an encryption-based
mechanism. Such a mechanism should include the content hash, and the provider’s identity and signature to
enhance the security of the content delivery system.
A provider can encrypt content and disseminate it with a cryptographic key. The client can retrieve the
encrypted content from a vCache or from the content provider itself. Upon reception of the encrypted
content, the client can then request the private key from the content provider, which decides whether or
not the client is legitimate. If the client is authorized to access the content, the key is encrypted with the
identity of the client and then sent to the client. Upon reception of the key, the client extracts the key to
decrypt the content.
Access Privilege Violation
An end-user can still retrieve popular content even if their access privilege to this content has been
revoked. Content origin server will not be aware of this access violation.
The addition of an access privilege only requires granting authorization to a new user by retrieving the
decryption key. However, to revoke a privilege, the content needs to be encrypted with a new key that is
then only made accessible to the set of users who remain authorized after the evolution of the policy.
To prevent access to revoked users, a security layer like ConfTrack-CCN [18] has recently been proposed that
allows users access an encrypted version of the content, forcing them to authenticate by directly contacting
the content producer for the decryption key. We believe that multi-layer encryption is a good approach that
should be further explored.
Content Access Trackability
In ICN, content is cached at intermediate routers that serve interests with objects regardless of the user
privilege. As the original content producer has no more control on the data it pushed in the network, it
raises new concerns, especially in terms trackability. Content providers are more and more interested in
tracking every access to their content (i.e., YouTube, Netflix) to avoid copyright problems or legal issues.
Moreover, content providers do not offer the possibility to fetch a local copy of content.
Cache Monitoring Attacks
A malicious user can monitor the behavior of other users in the same local cache (e.g., vCache, MoBcache).
Implementing smart caching policies and forwarding rules can prevent this.
2.5. ICN based content delivery in CHARISMA By using the ICN content distribution paradigm, the end user requests content from the network by sending
an interest message with the content name. The network delivers it from any node having a copy of the
content. This approach can seamlessly provide distributed in-network caching at any network level: each
intermediate node can make a local copy of the content that they are forwarding and serve the local copy to
CHARISMA – D3.3 – v2.0 Page 28 of 43
any subsequent request of the same content, thus moving replicas of the most popular content towards the
nodes closer to the end user without the need of any application-layer support, and even without support
from the content producer. ICN is therefore a tool capable of giving the network provider several operational
knobs to unleash the potential of a Fixed Mobile Convergence (FMC) access network. In practice, the network
can dynamically choose the best repository, route, and interface from which to serve any content or even
part of content.
2.5.1. Latency benefit
Low latency can be achieved by the caching and nearest replica routing infrastructure envisioned by ICN
solutions. ICN enables cache memories on the communication data path to improve service performance by
caching, especially caching popular content at network edge, which allows reducing retrieval latency. Every
ICN router manages a cache, storing previously requested objects in order to improve content delivery by
reducing the path length for popular content. If content is available locally in the cache, the router sends it
back directly to the requester; otherwise, it forwards the request to the next hop to find the nearest replica
in the network. In this way, in-network caching intrinsically relieves the fallouts of network distance or traffic
congestion. In ICN, in-network caching designed as a native building block of the network makes ICN to be
considered as a promising 5G-network technology.
Through the designs of latency-aware cache management mechanisms for ICN, the service latency can be
further improved as described in [10] [11]. The authors in [11] leverage the local latency in a distributed way,
to make the decision on whether to store an object in the network cache. The distance to bottleneck on a
per-flow basis has been taken into account, with the results showing that the content mean delivery time
can be reduced by up to 50%.
2.5.2. Mobility benefit
The ICN paradigm promises a wide set of qualitative and quantitative benefits, beyond the low latency and
traffic/load savings associated with caching. In the particular context of mobile networks, ICN promises the
simplification of mobility management. By shifting from the host-centric IP paradigm, ICN allows clients to
move across network locations without breaking existing communications sessions. In the case of the most
prominent ICN architecture, i.e., CCN/NDN, this is enabled by the fact that communication is inherently based
on a pub/sub, communication mode where a Data packet is delivered to a network location by consuming
trails established by a corresponding Interest packet (that serves the purpose of a request or a subscription).
As a result, communication sessions are not defined by the network locations of the involved clients, but
rather the trails (soft state) established by their request packets. Simply re-issuing pending requests promises
a quick diversion of data packets to the new location of a moving client. Such a capability obviously promises
lower disruption for mobile communications. It must be noted, however, that the same solution does not
apply in the case of a mobile content provider, necessitating a location management scheme as in traditional
mobile networks.
CHARISMA – D3.3 – v2.0 Page 29 of 43
3. Interface design of CHARISMA cache system
3.1. Overview and requirements of interface design In this section, we describe the interface designs of the different modules of the CHARISMA content delivery
system. As shown in Figure 2-2, there are three main components: Cache Nodes (including vCache and
physical cache), virtualized Cache Controller (vCC), EM, and cache components in the CHARISMA control,
management & orchestration (CMO). The interface designs of particular interest include:
Communication between cache nodes;
Interfaces between cache nodes and vCC;
Interfaces between VNFs (vCache and vCC) and VNF manager.
The interface designs between cache nodes mainly include two levels: communications between cache nodes
allocated to a specific VNO, and communications of cache nodes across different VNOs. Inside a VNO, through
collaborative caching solutions between the cache nodes distributed in the different aggregation levels (CALs)
of the network, the VNO is able to configure and manage their own cache nodes in order to optimize the
service latency and bandwidth consumption and improve QoS of their end users. The CHARISMA content
delivery system further enables the cooperative caching solutions between VNOs to achieve the potential
benefits of co-locations. Through a peering configuration of cache nodes based on an agreement between
the involved VNOs, the caches can be efficiently shared between VNOs that can achieve a further
improvement of their service provisions.
The interfaces between cache nodes and vCC are designed to allow cache controller configuring, and
managing the involved cache nodes. Each vCC is assigned to a specific VNO that is able to manage the
associated cache nodes, without interference from the CHARISMA infrastructure provider. Using the vCC, the
VNO can flexibly configure the cache algorithms, cache sizes, cached content type, etc. according to their
requirements. Furthermore, exchanging information between vCCs that have an overview of the cached
content allows cache sharing between VNOs and the monitoring data of the involved cache nodes.
In the CHARISMA content delivery system, the vCache and the vCC are implemented as VNFs by using
virtualization of caches and cache controller. The VNF manager integration interface is designed to integrate
between VNF manager and VNFs/Ems. For example, the set of VNF Manager interfaces captures the
operation that the VNF Manager needs to complete for VNF life cycle management. It also allows the VNF
Manager to update the vCC and vCache status.
3.2. Communication between cache nodes As mentioned in Section 0 multi-tenancy fosters the emergence of new relationships between VNOs, focusing
on the potential benefits of co-location. In the particular case of caching, these opportunities refer to the
opportunity for the support of cooperative caching across VNO administrative borders, in the form of cache
peering. Figure 3-1 presents an example setup of the envisioned scenario, for the simple case of two tenants
VNO 1 and VNO 2, which hold vCache instances on the same IMU. Content requests from UEs subscribed to
VNO 1 are delivered to VNO 1’s vCache instance at a certain IMU. Upon a cache miss, the request is re-
directed to the co-located VNO 2’s vCache instance. As the two vCaches are located within the same IMU,
the latency for the redirection of the content request is expected to remain at a low level, as the whole
operation is confined within the IMU.
CHARISMA – D3.3 – v2.0 Page 30 of 43
Figure 3-1: Example operation of vCache peering in multi-tenancy scenarios. A cache miss in the vCache
of VNO 1 results in the redirection of the content request to the vCache instance of the co-located VNO 2.
The technical realization of the vCache peering scenario builds upon the appropriate configuration of the
vCache instances of the involved VNOs. Well-established cache implementations, such as Squid, support such
configurations in the form of sibling caches 10. The element manager (EM) component of the CHARISMA
architecture is responsible for carrying out this configuration, as it takes place at the application level and is
specific to the particular VNF functionality.
Such a configuration, however, calls first for the establishment of a peering agreement between the involved
VNOs. Cache peering agreements are expected to take place in a fashion similar to peering agreements for
inter-domain traffic exchange, being established by out-of-band means. Service Level Agreements (SLAs) are
expected to document the exact terms of the agreement, including the load accepted by the peering caches,
expressed in terms of request/response rates, as well as the expected response times. In consequence,
appropriate monitoring of exchanged request and response (data) rates is performed by each vCache, with
the derived information being collected by the corresponding EM.
10 Upon a cache miss, a request can be redirected to another sibling or a parent cache. A parent cache will check its own parents/siblings if it does not have the requested item cached. A sibling cache will only check its local state, returning either the requested item itself or a negative response.
CHARISMA – D3.3 – v2.0 Page 31 of 43
3.3. Interfaces between cache nodes and cache controller The cache control and management is based on the NETCONF protocol. Network Configuration Protocol
(NETCONF) provides mechanisms to install, update, and delete the configuration of cache nodes distributed
in the network. The NETCONF server runs on cache nodes and the NETCONF client is installed in the cache
controller. Usually, the cache controller establishes a NETCONF session with cache nodes to obtain and
manipulate the configuration data.
The interface implementation should be done in both cache nodes and the cache controller. In the cache
controller part (NETCONF client), a Yang project needs to be created that can generate Java APIs from Yang
model files. In cache nodes, new TransAPIs need to be designed and developed to support a new
configuration operation. TransAPI is the interface through which the NETCONF server changes the setting of
various devices (e.g., network interfaces), the system (e.g., time zone), and the configuration of software
programs (e.g., Squid Proxy) on the machine. The possible configurations on a cache node that can be
managed by the cache controller include:
HTTP port of the cache node
Cache memory size
Cache memory replacement policy, like Least Recently Used (LRU) or Least Frequently Used (LFU)
Cache storage replacement policy
Maximum/minimum cached object size
Maximum opened disk file handlers
High/Low cache swap value
3.4. Interfaces to VNF manager
Section 2.2 presented an approach to the identification of traffic amenable to caching, with the purpose of
reducing latencies associated with cache misses. The model that was presented aims at handing over full
control of the overall functionality to VNOs, but not allowing them to expose sensitive information related
to the content access patterns of their customers to the infrastructure provider. In this respect, the SDN
controller and the vSwitches, that are enabling the traffic monitoring, management and control functionality
of the proposed scheme are realised as VNFs. In an alternative scenario, vCache is operated and managed by
the infrastructure operator itself, in a non-multi-tenancy context, with the purpose of enhancing the
performance of its own network. In this model, the design of the overall scheme can be simplified by placing
the corresponding functionality onto the existing components of the CMO architecture.
Figure 3-2 illustrates an example solution for this alternative model. In this case, the design is substantially
simplified, as the already deployed SDN components of the architecture are utilized. At the same time the
VNFM takes a central role in coordinating the overall scheme. This coordination is enabled by the delivery of
content access statistics from the EMs of the instantiated vCaches over the Ve-Vnfm interface; this
information describes the IP addresses where the cached content comes from. The VNFM is then responsible
for configuring the cacheable flows rules on the underlying (v)Switching components, by interacting with the
SDN controller within the VIM. This interaction takes place over the Vi-Vnfm interface.
CHARISMA – D3.3 – v2.0 Page 32 of 43
Figure 3-2: CHARISMA solution for cacheable traffic identification and handling (managed by the
infrastructure operator)
At the moment of writing this D3.3 deliverable, we have not yet decided whether the CHARISMA CMO will
make use of a single VNF generic VNFM, or implement a different VNFM for the management of each VNF,
which would require the implementation of one VNFM for the cache VNF, and another VNFM for the cache
controller VNF. Taking into account that CHARISMA implements four different VNFs, for efficiency reasons
the implementation or the adoption of a VNF-generic VNFM seems more appropriate.
Currently there is no standard interface between the VNFM and the VNFs (Ve-Vnfm), and the VNF developers
have the freedom to choose the technology that best suits their needs. However, independently of the
technology to be chosen, a VNF management interface should at the least be defined and implemented to
support the VNF lifecycle. All generic operations expected for the lifecycle management of a VNF should be
provided through this interface. These operations include:
Instantiate/Terminate VNF: The VNFM shall use this interface to instantiate a new VNF or terminate
one that has already been instantiated.
Retrieve VNF instance run-time configuration: The VNFM SHALL use this interface to retrieve the
VNF instance run-time information (including performance metrics).
Configure a VNF: The VNFM SHALL use this interface to (re-)configure a VNF instance.
Manage VNF State: The VNFM SHALL use this interface to collect/request the state/change of a given
VNF (e.g. start, stop, etc.).
Scale VNF: The VNFM SHALL use this interface to request the appropriate scaling (in/out/up/down)
metadata to the VNF.
CHARISMA – D3.3 – v2.0 Page 33 of 43
4. Overview of primitive implementation
4.1. Cache Nodes and Cache Controller
During the first year of the CHARISMA project, a primitive implementation and a first integration with other
modules has been undertaken. We have implemented the basic functions of the cache nodes (in a MoBcache
as shown in Figure 4-1, and as a VM) and the cache controller.
The MoBcache is a mobile router-server prototype enabling content caching and prefetching functionalities.
It has a built-in battery, and it configures itself automatically within a tree radio network. It has the following
interfaces:
1 GB Ethernet Port
1 Wi-Fi 5 GHz interface
1 Wi-Fi 2.4 GHz interface
1 optional LTE interface (to be added during the CHARISMA project)
Figure 4-1: The MoBcache prototype
A set of programs has been implemented and integrated in the software implementation, including Squid,
Prefetcher, Netopeer server, IPTABLES rules, etc., which have been described in Section 2.2.1. The MoBcache,
specially designed for mobile scenarios in the CHARISMA system to keep service continuity while a user
moves and makes hand-overs between networks, is implemented based upon OpenWrt and deployed at the
CAL0. Another version of a Cache Node based on Ubuntu has also been implemented and can be flexibly
deployed at different CAL levels in the CHARISMA infrastructure.
CHARISMA – D3.3 – v2.0 Page 34 of 43
The cache controller (implementation is based on Ubuntu) is deployed at CAL3. The CC is designed to manage
and configure all the CNs distributed in the network over the NETCONF protocol. The CC is responsible for
communicating with Netconf and external modules to configure CN and send controlling messages to the CN.
Figure 4-2: Diagram of the logical architecture
In the first integration as shown in Figure 4-2 that has been demonstrated in EUCNC 2016 in Athens (and
described in greater detail in the parallel deliverable D4.1), we have integrated the MoBcache prototype (L0
Cache) at CAL0 and an Ubuntu-based cache node (L1 Cache) at CAL2. The L0 Cache connects to the network
by Ethernet and provides WiFi 802.11 access to user equipment. The L1 Cache connects to the TrustNode
router by a 1 GbE link. The user equipment runs an Http Live Streaming video from the content server
connecting to TrustNode. The CC is deployed at the CAL3.
Table 2: Experimental results from the first integration
Without caches (s) With caches Improvement
HLS on UE
(3.4 Mbps video) 1.503 1.04 0.463
Wget by UE 1.502 0.945 0.557
We made two tests: 1) by VLS to play a video with 3.4 Mbps, and 2) by wget (a tool that retrieves content by
HTTP, HTTPS and FTP protocol) to retrieve the first chunk, with the cache and without the cache. The results
in Table 2 present the playback startup delay, that is the latency between sending a user request to starting
to play the video on the screen (i.e. get the first video chunk to play). The analysis is based on monitoring the
traffic using Wireshark. When we run VLC to play HLS video on user equipment without caches, the playback
startup delay is 1.503 seconds; whilst with caches near to the user, the delay is 1.04 seconds. The result
clearly shows the benefits of service latency (0.463 seconds and 0.557 seconds have been improved
respectively for the two tests) by deploying caches near to the end users.
Future implementation for the CHARISMA caching system is to virtualize the cache nodes and the cache
controller that are being managed by the CHARISMA CMO system. Then we can flexibly deploy vCaches and
vCC at the different CAL levels, according to the requirements of VNOs and the network status.
CHARISMA – D3.3 – v2.0 Page 35 of 43
4.2. VNF Descriptor
In this section we provide an example VNF Descriptor implemented in JSON. The VND presented in the listing
below follows the structure we defined in section 2.2.4. The definition of the cache node and cache controller
VNFDs is currently work in progress; however, their final versions will follow a similar structure to the one
we provide below.
{
"provider": "NCSRD",
"id": 1,
"type": "cache node",
"description": "The cache node (CN) is responsible for caching the appropriate HTTP
content and delivering it to end users that have requested it",
"name": "Cache_Name",
"created_at": "2016-01-29T04:44:22Z",
"modified_at": "2016-01-29T04:44:22Z",
"vdu": [
#1 vdu
{
# Image repository download link
"vm_image": "http://192.168.1.2/images/cache0.img",
"vm_image_md5": "2345094b3b92832abb35162a61f6aa03",
"vm_image_format": "raw",
"id": "vdu0",
"alias": "cache0",
# Resource requirements
"resource_requirements": {
"hypervisor_parameters": {
"version": "10002|12001|2.6.32-358.el6.x86_64",
"type": "QEMU-KVM"
},
"network_interface": {
"bandwidth_unit": "",
"bandwidth": "",
"card_capabilities": {
"SR-IOV": true,
"mirroring": false
}
},
"storage": {
"size_unit": "GB",
"persistence": false,
"size": 80
},
"memory":{
"size_unit": "GB",
"persistence": false,
"size": 8,
"additional_parameters": {
"large_pages_required": false,
"numa_allocation_policy": ""
}
},
CHARISMA – D3.3 – v2.0 Page 36 of 43
"cpu":{
"vcpus": 8,
"hardware_acceleration": "AES-NI"
}
},
"connection_points": [
{
"vlink_ref": "management_net",
"id": "mngt0"
},
{
"vlink_ref": "internal_net",
"id": "int0"
}
],
# Monitoring Parameters
"monitoring_parameters": {
"generic": ["cpu", "memory_total", "memory_free", "memory_used", "disk_io",
"disk_free", "bps_in", "bps_out", "packets_in", "packets_out", "errors", "dropped"]
"specific": ["number_of_http_requests_received", "cache_hits_percentage_for_5
minutes", "cache_disk_utilization" , "cache_memory_utilization",
"number_of_users_accessing_cache"]
},
# Number of vms
"scale_in_out": {
"minimum": 1,
"maximum": 4
}
},
#2 vdu
{
"vm_image": "http://192.168.1.2/images/cache1.img",
"vm_image_md5": "2345094b3b92832abb35162a61f6aa03",
"vm_image_format": "raw",
"id": "vdu1",
"alias": "cache1",
# Resource requirements
"resource_requirements": {
"hypervisor_parameters": {
"version": "10002|12001|2.6.32-358.el6.x86_64",
"type": "QEMU-KVM"
},
"network_interface": {
"bandwidth_unit": "",
"bandwidth": "",
"card_capabilities": {
"SR-IOV": true,
"mirroring": false
CHARISMA – D3.3 – v2.0 Page 37 of 43
}
},
"storage": {
"size_unit": "GB",
"persistence": false,
"size": 80
},
"memory":{
"size_unit": "GB",
"persistence": false,
"size": 8,
"additional_parameters": {
"large_pages_required": false,
"numa_allocation_policy": ""
}
},
"cpu":{
"vcpus": 8,
"hardware_acceleration": "AES-NI", # Not sure about this
},
"vswitch_capabilities": {
"type": "ovs",
"version": "2.0",
"overlay_tunnel": "GRE"
}
},
"connection_points": [
{
"vlink_ref": "monitor_net",
"id": "mon0"
},
{
"vlink_ref": "internal_net",
"id": "int0"
}
],
# Monitoring Parameters
"monitoring_parameters": {
"generic": ["cpu", "memory_total", "memory_free", "memory_used", "disk_io",
"disk_free", "bps_in", "bps_out", "packets_in", "packets_out", "errors", "dropped"]
"specific": ["number_of_flows", "number_of_flows_classified", "dropped_packets"]
},
# Number of virtual machines
"scale_in_out": {
"minimum": 1,
"maximum": 2
}
}
],
"vnf_lifecycle_events": [
{
"authentication_username": "ubuntu",
"driver": "ssh",
CHARISMA – D3.3 – v2.0 Page 38 of 43
"authentication_type": "PubKeyAuthentication",
"authentication": "<<SSH KEY>>",
"events": {
"start": {
"command": "service xxx start",
"template_file": "<< lifecycle event template >>",
"template_file_format": "JSON"
},
"stop": {
"command": "service xxx stop",
"template_file": "<< lifecycle event template >>",
"template_file_format": "JSON"
},
"restart": {
}
}
}
]
}
CHARISMA – D3.3 – v2.0 Page 39 of 43
5. Conclusions
In this deliverable D3.3, we have defined and specified the initial CHARISMA content caching solutions and
traffic handling methods arising from the Task 3.4 “Content Caching and Traffic Handling at the RAN node”
of work package WP3 during the first year of the CHARISMA project. The main objectives of the CHARISMA
content caching system are to reduce service latency by deploying caches near to end users and provide open
access service by virtualization of the caches and cache controller. We have also discussed the security issues
related to caching, with the initial designs of the security solutions to be undertaken in the future work of
T3.4 in the second year of the project.
The CHARISMA caching system provides two kinds of caches: JCP-Connect’s MoBcache system with an
advanced design of the hardware devices to provide a seamless service in a mobile 5G scenario; and SDN-
based virtualized caches providing dynamic deployments. The CHARISMA caching system provides open
access and multi-tenancy services by allocating virtualized caches and the virtualized cache controller to a
Virtual Network Operator (VNO) depending on the VNO’s requirements and network status.
In order to optimize service latency through the use of caching solutions, this deliverable has also further
analysed the operation of such caches, e.g. also by identifying appropriate traffic cacheability. By identifying
the UE flows amenable to caching, selective traffic offloading can be deployed to remove unnecessary
caching operations and therefore reduce the service access time latency. Each of the different Converged
Aggregation Levels (CALs) of the CHARISMA architecture have also been identified as a distributed caching
location, so that the MoBcache system provides a virtualised and intelligent seamless service in a future 5G
scenario requiring mobility.
The CHARISMA caching system is managed by the CHARISMA control, management and orchestration (CMO)
system, such that the virtualized caches and virtualized cache controller are dynamically
created/deleted/reconfigured by the VNF manager and orchestrated by service orchestrator. Furthermore,
the CHARISMA caching system allows VNOs to autonomously configure, deploy and manage their own
allocated virtualized caches by the virtualized cache controller, without intervention from the complete
CHARISMA platform.
The first implementation and integration with the other low latency technologies in the associated
intermediate demonstrator has also been performed, and reported in the parallel deliverable D4.1. Future
developmental work on the MoBcache in the second year of the CHARISMA project will be directed towards
the design and implementation of the virtualization of caches and cache controller, and to full interfacing
with the CHARISMA CMO plane. In addition the integration of the CHARISMA content caching system into
the project pilots for the end of the project will also continue to be pursued.
CHARISMA – D3.3 – v2.0 Page 40 of 43
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CHARISMA – D3.3 – v2.0 Page 42 of 43
Acronyms
AP Access Point
API Application Programming Interface
BRAS Broadband Remote Access Server
CAL Converged Aggregation Level
CC Cache Controller
CDN Content Delivery Network
CDNi Interconnection of Content Distribution Networks
CMO CHARISMA Management & Orchestration
CNs Cache Nodes
COTS Commercial off-the-shelf
CP Cache Proxy
DB Database
DPI Deep Packet Inspection
DSL Digital Subscriber Line
DSLAM Digital Subscriber Line Access Multiplexer
EM Element Manager
FMC Fixed Mobile Convergence
FTTB Fiber to the Building
FTTH Fiber to the Home
HTTP Hypertext Transfer Protocol
ICN Information Centric Networks
IP Internet Protocol
JSON JavaScript Object Notation
LFU Least Frequently Used
LMP Local caching Management Primitive
LRU Least Recently Used
LTE Long Term Evolution
NCS NetConf Server
NAT Network Address Translation
NETCONF Network Configuration Protocol
NFV Network functions virtualization
OTT Over the Top
CHARISMA – D3.3 – v2.0 Page 43 of 43
PFP PreFetch Proxy
QoS Quality of Service
QoE Quality of Experience
RPC Remote Procedure Call
RTT Round-Trip Time
SDN Software Defined Networking
Service M&A Service Monitor and Analytics
SGW Serving Gateway
SLA Service-Level Agreement
SP Service Providers
UE User Equipment
vCache virtual Cache
vCC virtual Cache Controller
VDU virtual Deployment Unit
vRouter virtual Router
vSwitche virtual Switch
VoD Video on Demand
VM Virtual Machine
VNF Virtual Network Function
VNFD VNF Descriptor
VNO Virtual Network Operator
XML Extensible Markup Language
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