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NTT Network Service Systems Laboratories
Management of managed self-organizing network in
network virtualization environment
WTC 2012 @ Miyazaki, Japan
Takashi Miyamura1 Yuichi Ohsita 2 Shohei Kamamura1 Yuki Koizumi2
Shin’ichi Arakawa 2 Kohei Shiomoto1 Atsushi Hiramatsu1 Masayuki Murata 2
1 NTT Network Service Systems Laboratories 2Osaka University
NTT Network Service Systems Labs.
Outline of Talk
•Background
•Problem Statement
•Proposal: Managed self-organization
•Evaluation
•Conclusion
2
NTT Network Service Systems Labs.
Outline of Talk
•Background
•Problem Statement
•Proposal: Managed self-organization
•Evaluation
•Conclusion
3
NTT Network Service Systems Labs.
Overview of Managed Self-Organizing Network
• Aim: Simplify management of network virtualization infrastructure through self-organization
• Challenge: Performance degradation due to resource contention • Proposal: Architecture for stable accommodation self-organizing VNs
4 Optical infrastructure
(physical networks)
PN Resource Manger
VN Agent Controller
VN Agent
VNT derived by Attractor selection
Traffic IN
Traffic OUT
gene1
gene2
gene3
gene4
substrate1
substrate2
substrate4
substrate3
diffusion metabolic network
metabolic reaction
catalyzation
growth rate
diffusion
Bio-model gene regulatory network
VN#1
VN#2
VN#3
Virtual networks
VNT Agent
VNT Agent
VNT Agent
VN quality
monitoring Indirect
control
Feedback to activity
Performance
monitoring
Performance monitoring
Activity
VN: Virtual network
PN: Physical network
NTT Network Service Systems Labs.
Background
• Network Virtualization provides controllability for users
• Users freely designs own topology for adaptability
• Introduce biology-inspired topology control scheme (=self-organization)
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PN Resource Manger
VN#1
VN#2
VN#3
VNT Agent
VNT Agent
VNT Agent
Biological system
Biological system
VN topology designed by users
NTT Network Service Systems Labs.
Adaptive VNT reconfiguration
Optical Path
IP Packets
VNT
Congestion
collect link traffic measurement
Estimate Traffic matrix
Calculate Optimized VNT
Reconfigure Optical paths
Measurement
Teardown Setup
Control PN Manager
OXC Router
VN Agent
VNT: Virtual Network Topology 1. Initial Topology
1. Optimized Topology
NTT Network Service Systems Labs.
Background: Attractor selection-based control
1. Adaptability to unknown environmental changes – System finds attractor (=equilibrium point) through random search to adapt
environmental changes.
2. Simplicity of control mechanism – Light-weight computation to find solutions
– Works well with limited information.
Gene regulatory network (=Virtual networks)
Metabolic network (=Physical network) [Kashiwagi2006] Kashiwagi et al.,”Adaptive Response of a Gene Network to Environmental Changes by Fitness-Induced Attractor Selection ,” PLoS ONE, vol.1, 2006.
Differential equation
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NTT Network Service Systems Labs.
Outline of Talk
•Background
•Problem Statement
•Proposal: Managed self-organization
•Evaluation
•Conclusion
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NTT Network Service Systems Labs. Our goal
•Establish resource management architecture for accommodating numerous VNs.
Some Design Principles
–Each VN is controlled according to self-organization for quick responsiveness.
•VNs can freely aquire/delete virtual resources from PN for constructing optimal topology.
–Minimal Control: Ensure enough scalability in terms of network size and the number of VNs.
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NTT Network Service Systems Labs.
Problem we are solving
• High-performance network virtualization over optical network infrastructure.
– Wavelength path between two V-nodes fomrs virtual link in VNT.
– Dedicated wavelength resource is allocated to each VN for hard isolation.
• Key Question: Physical resource are limited. How to solve resource contention among numerous VNs? – Introduce minimal intervention for stability.
⇒ Design simple management architecture for self-organizing VNs.
10 Optical network Infrastructure L1 Switch
L2 Switch
L3 Switch
VN#3 VN#1 VN#2
Virtual Resource Allocation
contention
Self-Organization
VNT 1* VNT 2
contention
NTT Network Service Systems Labs.
Outline of Talk
•Background
•Problem Statement
•Proposal: Managed self-organization
•Evaluation
•Conclusion
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NTT Network Service Systems Labs.
Our concept: Managed Self-Organizing System
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Self-Organizing System (SOS)
Has an ability to operate in a dynamically
changing environment without centralized
control.
Managed Self-Organizing System
Provides a range of operating regime by an
external control while allowing a self-
organization property
Self-organizing system
Self-organizing elements
Emergence???
Self-organizing elements
Self-organizing system
Controller Observation Control
• Limitations: Applying self-organization to multiple elements (i.e., VNs) can cause instability in case of emergency.
• Our solution: Introduce minimal control in resource allocation.
Fully distributed system
Hybrid control system
NTT Network Service Systems Labs. Design approach
• How to ensure scalability of resource management? – To accommodate hundreds of VNs, we should avoid fully centralized control.
– Introduce indirect control for resolving resource contention among self-organizing VNs.
• Key observation for resource contention. – Same algorithm based on same information often cause synchronization.
⇒ Inform different residual information to each VN for diversification.
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Under-utilized
Congested
Moderate
Moderate #2 #1
#2 #1
#2 #1
#2 #1
Initial state After control (Change topology awareness)
Link #1 Link #1
Link #1
Link #2
Link #1
Link #2
VN VN
VN #1
VN #2 VN #2
VN #1
λ paths
λ paths
NTT Network Service Systems Labs.
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PN Resource Manager
Resource management model
Resource management system controls topology-awareness to each VN to avoid resource contention while allowing resource sharing to some resources. – Each VN utilize resources with “Right-to-use” privilege.
– By combining resources with privilege, VN topology is created on-demand.
⇒ Virtual resource layer enables indirect control of self-organizing VNs.
VN#1 VN#2
Physical Link 1 Physical Link 2
λ1
λ2
λ3
λ4 VN#1
VN#1
VN#1
VN#1
VN#2
VN#2
VN#2
VN#2 VN#2 Dedicated
VN#1,#2Shared
VN#1Dedicated
VN#2
Assign Right-to-use to each wavelength
VN#2
VN#2
VN#2 VN#2
VN#2 VN#1
VN#1
VN#1
VN#1
Link 1 2
VN is aware and can use resources with Right-to-use.
Physical resources
aware to VNs
VN
Virtual resource layer
PN VN#1
VN#1
Link 1 2
VN#2
VN#2 VN#1
VN#1
NTT Network Service Systems Labs.
Procedures for avoiding contention
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Physical
Link 1
Physical
Link n
Lambda 1
Lambda 2
Lambda 3
Lambda 4 VN#1
VN#1
VN#1
VN#2
VN#2
VN#2
VN#2
VN#2
VN: Virtual Network
VN#1
VN#2
VN#2 VN#2
VN#1 VN#1
Shared Resource
③ Regulate resource view •Regulate residual resource view for outperformed VN. •Allocate reserved resources for congested VN.
① Initial State •All resources are shared by VNs •VN can user every resource for constructing topology
VN#1
VN#2
② Monitoring VN performance •Link load of VN is monitored. •If max load exceeds threshold, we considfer resource contention occurred.
VN#1 VN#2
NTT Network Service Systems Labs.
Outline of Talk
•Background
•Problem Statement
•Proposal: Managed self-organization
•Evaluation
•Conclusion
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NTT Network Service Systems Labs.
Experimental Demonstration
• Developed network emulating systems for demonstrating our architecture. – Simulate behavior of multiple self-organizing VNs.
– Generate traffic demand changes and topological failures.
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Network Emulator
PN resourceManager (DUT)
VN Agent (DUT)
Algorithm VN topologyLink load PN Resources
DUT: Device under testPN: Physical networkVN: Virtual network
Physical network
GUI System
VN Emulation
function
PN Emulator
function
Traffic Generator
VN DB
Virtual Networks
NTT Network Service Systems Labs.
Result 3: Asymptotic behavior
• Evaluate performance in simple 11-nodes Abilene topology. – SO fails to avoid resource contention.
– Proposed mechanism quickly recovered performance by reallocating resources.
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Completely Self-organized control
allocation
Proposed (Managed SO control)
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Traffic changes Resource reallocation
VN#1
Link load
activity
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Traffic changes
VN#1
NTT Network Service Systems Labs.
Outline of Talk
•Background
•Problem Statement
•Proposal: Managed self-organization
•Evaluation
•Conclusion
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NTT Network Service Systems Labs.
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Concluding remarks
•Summary:
–Propose managed self-organizing network architecture
•VNs controlled based on biological systems.
•Require some mechanism for alleviating resource contention among VNs.
–Basic idea is to regulate resource view for hot spot links
–Simulation study demonstrated effectiveness of proposed algorithm
•Quickly recovered performance due to sudden traffic change
• Future work:
–Evaluate computation overhead of DRAMS.
–Evaluation in large-scale network, more than 3 VNs.
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NTT Network Service Systems Labs.
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Thank you
for your attention
Acknowledgement:
This work was supported in part by the SCOPE (Strategic
Information and Communications R&D Promotion Programme) of
the Ministry of Internal Affairs and Communications, Japan.