Friday, 30 October 2015 1

Placing Content Intelligence at 5G Mobile Network Edge

Ning Wang

University of Surrey

Confidential – for 5GIC Members Only

5G Innovation Centre (5GIC) Vision on 5G

Wednesday, 04 November 2015 2

Mobile application content/data+

Context information

“User perceived infinite bandwidth capacity”

5GIC’s two complementary solutions:

• Efficient use of radio spectrum

• Intelligent network handling of data

DATA

Confidential – for 5GIC Members Only

Our Research Landscape

Wednesday, 04 November 2015 3

Context awareness

Content/context aware 5G network architecture

Network support

Context (knowledge) input

User context

Co

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xt

da

ta e

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ing

Content context

Applications

Optimisationtargets

• Multimedia content• Internet of things (IoT)

• Enhanced User experiences

• Network efficiency• Device efficiency

Network functions• Discovery / retrieval• Caching / pushing / adaptation• Routing /forwarding• Context data analytics

Network context

Device context

Confidential – for 5GIC Members Only

Intelligence on Video Content Handling: Network edge vs. Devices

Wednesday, 04 November 2015 4

Content source

(DASH server)

Cached DASH segments with

different resolution levels

Mobile

network

Knowledge on:

Content, users, devices

and network conditions

OTT delivery

Context information on:

Smart decision making by 5G devices – adaptively control video content downloading across parallel available RATS, based on the provided network context

Smart decision making by 5G Network, based on Mobile Edge Computing (MEC) –content caching and active pushing towards UEs, based on the provided device context (e.g. buffer level)

Network context

User/device

context

Confidential – for 5GIC Members Only

Mobile Edge Computing (MEC) Enablement

Wednesday, 04 November 2015 5

Goals

To leverage MEC as a key enabler for supporting smart network

operations in different mobile applications

MEC functions

Video content caching

Video adaptation and pushing

Enables

Metadata caching and processing for

web content

Proximity service control for D2D

networking

Minimise video access delay

Enhance video quality

Minimise web downloading

time

Smart not-spot coverage

Bring content close to users

Reduced RTT increases

TCP throughput

Actively feed UE with

optimised resolution levels

Connection optimisation based

on cached metadata

User mobility tracking and

prediction

Confidential – for 5GIC Members OnlyWednesday, 04 November 2015 6

Device-to-Device Networking in 5G

• Background: devices as part of 5G network

• Use case 1: Not-spot network coverage through D2D relay:– A “foreign” device makes a request for network access through D2D links

and local devices in proximity become helper candidates– Supported with decision-making algorithms on helper selection by

the client according to specific requirements and context information (e.g. client/helper mobility)

• Use case 2: D2D content caching: Pushing information centric networking (ICN) to the device level– Popular mobile content objects are pre-loaded a priori to a (small) set of

helper candidates to be disseminated to encounter clients in a opportunistic way

– Content requests originated from clients are sent to the ICN-supported network which is able to direct requests to the in-proximity helpers holding the content

– Supported with optimisations on (offline) helper selections and (online) content pushing/replacement at the helper device level

Confidential – for 5GIC Members OnlyWednesday, 04 November 2015 7

How MEC Plays a Role?

• User (helper) mobility – a double-edged sword

– Offers opportunities to get clients connected through D2D

– Causes connection disruptions/churns due to ad hoc departure

• Network’s knowledge on local mobile user mobility

– Capability of predicting the mobility behaviours of local connected users as potential helpers

– Practicality considerations: accuracy of human mobility prediction

• 80% - 93% spatiotemporal predictability of human mobility according to [1]

• Network’s intelligence

– Capability of computing the best combination of helpers in order to satisfy clients requirements, in particular towards minimised disruption

[1] Chaoming Song et al, “Limits of Predictability in Human Mobility”, Science, Vol. 327, 2010, pp. 1018-1-21

Confidential – for 5GIC Members OnlyWednesday, 04 November 2015 8

Summary

• In order to achieve “user perceived infinite capacity”, smart network functions need to be in place for complementing the radio technologies

• At 5GIC We envisage a wide variety of mobile services that can potentially benefit from MEC

– Content based: including both video- and web-based applications

– Non-content based: e.g. network-assisted D2D networking

• What can be smart network functions offered from MEC?

– Direct involvement of handling data/content in the user plane: e.g. caching, adaptation, pushing, prefetching etc…

– Smart control/coordination based on locally maintained context knowledge: e.g. D2D helper identification