NOVEMBER 2013

NOVEMBER 2013 WTD-ICMC-USP

Supporting the Brave New World of the 4As: Anytime, Anywhere,

Anyhow and Anything

Glenford MappAssociate ProfessorMiddlesex University

United Kingdom


Outline of My Talk

What is this new world really about

What are the challenges

Y-Comm – a bridge to this new world

Collaborations

What's new in my world

Joining the revolution


Anytime, Anywhere

Anytime It's a generational thing

Anywhere Actually I want to be able to communicate from

anywhere in the universe. • So I will need to spawn networks and connect

them to existing networks

• Building, managing and controlling networks should be under user control


AnyhowWe are seeing the rise of new networks based

on different technologies• Wi-Fi, WiMax, 4G, Ultrawideband, Optical

Networks, etc

We are also seeing new types of networks• Delay Tolerant Networks (DTNs)

• Home Networks, Personal Area Networks,

• VANETs – Vehicular networks

• Infrastructural networks: Sensor Networks

• E-Health Networks: Patient monitoring

• Social Networks:- Interaction between people


AnythingMost important of all

because a network is only useful if it is being used to carry information that people want

Content is King Monitizing content – directly or indirectly - is the

new El Dorado.

A massive paradigm shift in terms of what the Internet is being used for: Multimedia, interactive games, real-time

communication in all forms Low latency financial applications


The Key Challenges of Building this Brave New World

Very different to the current Internet

Support for mobility and location management is of primary importance Seamless, uninterrupted communication Handover must be controlled and managed Where you are may be used as a hint to where

you may be in the futureProactive approachKnow where network infrastructure is locatedPrivacy of Location Information


Challenges in Networks

How do we get networks to work together seamlessly Heterogeneous Networking Need a standard for ubiquitous handover between

networks at a low level Need to allow higher levels (transport

protocol/application) to adapt Multi-homing: managing all the network interfaces

on a device


Challenges in QoS

As traffic is increasing we need to look at some sort of Quality-of-Service support Lots of research into Internet QoS models

• IntServ:- failed because it could not scale

• DiffServ:- Works in the core network but not fine-grained enough to work on the periphery.

• Need a new approach


Challenges in Security

Security must be also a key issue of the Future Internet Current Internet is woefully inadequate

• Edward Snowden

Multi-level security Authentication, authorization Denial of Service attacks Privacy (use of the net not monitored)

Security needs to be built in from the start


Challenges of Big Data

New networks are producing data faster than we can analyse, categorize or process

Storage will also become a big issue

Data Security: who owns my data in the Cloud, who can access my data, do I have any say where the data is stored

Results of Big Data

– Information is now gold


Challenges of Service Delivery

Delivering services will also need to change

Services need to be managed in a more autonomous manner

Spawn new server instances at different locations or migrate services when required in response to:

– Geographical load patterns

– User mobility

– Network failure or recovery


Challenges of Different Types of Networking

Opportunistic Networking

– Taking advantage of social interaction; sensor networks

Move towards more data-centric paradigms

– Current Internet still communication-centric• Stresses host-to-host communication

Information Centric Networking

– Getting information – irrespective of location• Publish and subscribe models


Meeting these challengesNeed an integrated approach

– Cannot study one challenge in isolation

Failure is not an option

– Internet is the most successful thing that humans have made; the wheel is a distant second• Problems are building up and need to be

addressed

Affects all of us

– No country, institution or company should be in total control of the Internet


How are we going to make this happen – what is the approach

Revolutionary Approach Start from scratch

• Clean Slate Project; Plan 9 test

Evolutionary Approach Only incremental increases

• IPv6, INTERNET 2

Challenges mean that an evolutionary jump is needed


How are we going to make this happen – what is the approach

Try what has worked before

Agree on functionality; but not on implementation

Need a framework that gives us functionality but not say how the functionality is implemented

– Worked for telephony; 3KHz standard

– Worked for the Internet: OSI; TCP/IP


Why do you need a framework?

To be able to think about the issues coherently

Imposes mental discipline

– Forces you to always keep the Big Picture in mind

Separates functionality/policy from mechanism

Frees us to:• Use or enhance existing mechanisms/standards

• Only design new mechanisms when needed

HARDWARE PLATFORM (MOBILE NODE)

HARDWARE PLATFORM (BASE STATION)

NETWORK ABSTRACTION (MOBILE NODE)

NETWORK ABSTRACTION (BASE STATION)

HANDOVER MANAGEMENT

MOBILITY MANAGEMENT

END SYSTEM TRANSPORT

QOS LAYER

APPLICATION ENVIRONMENTS

CONFIGURATION LAYER

NETWORK MANAGEMENT

CORE TRANSPORT

NETWORK QOS LAYER

SERVICE PLATFORM

CORE NETWORKPERIPHERAL NETWORK

SAS

NTS

NAS

QBS

SECURITY LAYERS


A very brief Introduction to Y-Comm

This is not a talk about Y-Comm

Talks, papers at: http://www.mdx.ac.uk/research/science_technology/informatics/projects/ycomm.aspx

In essence Y-Comm is an architecture that is trying to integrate:

• Communication

• Mobility

• QoS

• Security


Y-Comm: Still a work in progress

It is not the only architecture that is being studied

– Ambient networks

– Mobile Ethernet

Y-Comm is by far:• The most detailed

• The most integrated

Architecture is stable• Recently tweaked some names of the layers to

make their functionality better understood by the mobile telcoms community


Why is Y-Comm differentY-Comm was predicated on two key

assumptions:

Network Evolution

– The Internet is decomposing into 2 components• A super-fast core using Optical Switching/MPLS

• Wireless Peripheral Networks at the Edge

Devices will have multiple Interfaces• 3/4G, Wi-Fi, WiMax, etc

• Called HETNET devices

Both the assumptions turned out to be true

BACKBONE

ACCESS NETWORKS

WIRELESS NETWORKS

Current Internet Future Internet

The Core Framework

SERVICE PLATFORM LAYER

NETWORK QOS LAYER

CORE TRANSPORT SYSTEM

NETWORK MANAGEMENT LAYER

CONFIGURATION LAYER

NETWORK ABSTRACTION LAYER

HARDWARE PLATFORM LAYER

The Peripheral Framework

APPLICATION ENVIRONMENTS LAYER

QOS LAYER

END TRANSPORT SYSTEM

MOBILITY MANAGEMENT LAYER

HANDOVER MANAGEMENT LAYER


HARDWARE PLATFORM LAYER


History of Y-Comm

Pre-Y-Comm (1998-2003)

– Cambridge Wireless Testbed

2006 – Peripheral Framework announced

2007 – Y-Comm architecture announced

2008 – USP & UFSCar join effort

2010 – Loughborough University joins effort

2012 – Lancaster University joins effort


Key People in Y-Comm

Glenford Mapp (Middlesex University)

Jon Crowcroft (University of Cambridge)

Edson Moreira (USP)

Helio Guardia (UFSCar)

Raphael Phan (Loughborough University)

Qiang Ni (Lancaster University)


Key PhD students

Fatema Shaikh (Middlesex University 2010)

David Cottingham (University of Cambridge 2010)

Renata Porto Vanni (USP 2010)

Mahdi Aiash (Middlesex University 2012)

Rigolin Lopes (USP 2012)

Mario Augusto (USP 2012)

Fragkiskos Sardis (Middlesex University)

Ann Samuels (Middlesex University)


Key Middlesex MSc Students

Diti Dave (2010)

Naveen Chinnam (2011)

Ali Mofidizati (2012)

Rajesh Lakkineni (2012)

Brian Ondiege (2012)

Eghe Akenuwa (2013)

Eric Ghokeng (2013)


What are the major contributions of Y-Comm so far

Handover

– Handover Classification; Proactive vertical handover, Calculations for NDT and TBVH

Security

– Integrated Security; Targeted Security Models;

Ontologies for Communication Architectures

– Y-Comm Ontology, MyHand

Quality-of-Service

– New QoS Framework


Things being worked on – NOT part of this talk

An implementation of IEEE 802.21• To provide seamless handover (UFSCar)

Game Theory in Communication Systems• To see if game-theory can lead to optimum

resource allocation (Lancaster University)

A new transport protocol for LANs• To optimize server speeds in LANs and Clouds

(Middlesex University)

A Hybrid Internet QoS model• Combining IntServ and DiffServ (Middlesex

University


End of Y-Comm PartY-Comm has been a success because it has

provided a framework to allow us to begin to exploring how to support the 4As

– Just a start; still a very long way to go before we get to this new world

Y-Comm has moved from the design/architectural phase to the implementation phase

– Exploring using Software Defined Networking (SDN) as a way of building a full Y-Comm prototype


Questions on Y-Comm


Going Deep

In this section we want to look at how a section of the work in Y-Comm is impacting 3 key areas:

– Resource Management in Core Networks

– Mobile Services

– VANETs

Need to understand proactive handover in Y-Comm


Basic Handover TermsHard vs Soft Handover

– Hard:- break before make

– Soft:- make before break

Network vs Client Handovers

– Network-based

– Client-based (Apple's Patent)

Upward vs Downward

– Upward – smaller to bigger coverage

– Downward – bigger to smaller coverage

Handover ClassificationHANDOVER

IMPERATIVE ALTERNATIVE

REACTIVE PROACTIVE

KNOWLEDGE-BASED MODEL-BASED

NETPREF

USERPREF CONTEXT

SERVICES

UNANTICIPATED ANTICIPATED

Knowledge-Based Proactive Handover (Cambridge)


Model Based Proactive HandoverThe work of Fatema Shaikh

Define a circular area of coverage called the Handover radius

Define a smaller radius called the Exit Radius at which handover must start in order for the handover to be completed at the Handover Radius

The time the mobile node has before it hits the Exit Radius is called Time Before Vertical Handover or TBVH


Threshold Circle coverage

Real coverage

Exit coverage

Exit threshold circle

Handover threshold circle

Model-Based Handover

Predictive Mathematical Model for TBVH(Simple Case)

• Introduction of additional functionality to Base Station at network boundary (BBS).

• Distance between MS and BBS derived from location

co-ordinates or

• Estimated TBVH

Movement of MS under BBS coverage (upward vertical handoff)

Simulation and Results

TBVH simulation in OPNET Modeler:


Why is TBVH important

If the Mobility Management Layer can calculate TBVH, it can signal to the higher layers that a handover will occur after a certain time so these layers can take action.

– Minimize the effects of handover delay and packet loss by buffering and using fast retransmission techniques

– It makes proactive handovers more seamless compared to reactive handovers• Can Fatema Shaikh's work be extended to any

arbitrary situation?

A

B

C

S

T

NET A

NET B

NET C

Combining Transport and Communications to determine the optimum handover

A

H1

C1

C2B

Y1Z1

E1

Y2

Z2

C

Y3

Z3

H3

E2

E3

S

TH2

Analysis shows that it is possible to calculate these key points with some degree of accuracy

Results


What does it all mean?If the mobile node knows: its location,

direction and velocity

– Via GPS or accelerometers

The location of the networking infrastructure

– Type of access network, the position of the access points

Good estimation of the Handover Radius

Then we can calculate the optimal times to handover over a large region (a few miles)

WIRELESSNETWORK

REQ (Time , TBVH, NDT)A

A

REQ (Time , TBVH, NDT)

B

B


Rethink Allocation Strategy

MNA needs channel at (Time + TBVH) A

MNA releases channel at (Time + TBVH + NDT)A

MNB needs channel at (Time + TBVH)B

MNB releases channel at (Time + TBVH + NDT)B


There are 3 possible outcomesNo contention:

• (Time + TBVH)A < (Time + TBVH)B

• (Time + TBVH + NDT)A < (Time + TBVH)B

Contention: Two Types: Partial and Total

• (Time + TBVH)A < (Time + TBVH)B

• (Time + TBVH + NDT)A > (Time + TBVH)B

• Partial Contention:

• Total Contention:

(Time + TBVH + NDT)A < (Time + TBVH + NDT)B

(Time + TBVH + NDT)A >= (Time + TBVH + NDT)B


Request SummaryRequests granted as requested:

– Channel granted at (Time + TVBH)A

– Channel released at (Time + TBVH + NDT)A

– Same with B

Requests granted but modified for B

– Channel granted at (Time + TBVH + NDT)A

– Channel released at (Time + TBVH + NDT)B

Request for B not granted:

– Force B to handover to another network


Further Results

Simulation results show that there is a clear benefit to using this approach

Nodes that can use the channel are not forced to wait behind nodes that cannot use the channel

Nodes that cannot use the channel quickly handover to other networks so we avoid unnecessary handover attempts

Good result for operators


Mobile Services

PhD research by Fragkiskos Sardis

General idea: as the users of a service move around the latency between the user and the service could increase such that the user's QoE could be affected

A way around this is to be able to migrate or replicate the service at a location closer to the mobile user to reduce latency

– Cloud Services now make this possible


Key Issues

What is the condition that indicates that movement of the server should be considered

– Latency/Bandwidth Threshold

What is the algorithm which decides to which Cloud should the service be migrated or replicated

There is a cost for moving the service which cannot be ignored

We need a service delivery framework

The Service Delivery Framework

SERVICE MANAGEMENT LAYER

SERVICE SUBSCRIPTION LAYER

SERVICE DELIVERY LAYER

SERVICE MIGRATION LAYER

SERVICE CONNECTION LAYER



Key Observation

Whether I move the service to a Cloud on the network to which the user is currently connected depends on how long the user is expected to be in that network

– Network Dwell Time or NDT

So the win is:

– The bytes saved running the service locally – the bytes needed to migrate the service

– First parameter is dependent on NDT


How could we test this

We set up a gaming scenario between a mobile device and two Clouds.

We begin playing the game on one Cloud and then signal to the system to migrate the game to the second Cloud.

When we migrate to the new network, we measure the bytes saved vs the amount of time I am in the network of the second Cloud


Results

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Further Work

NDT is crucial for good migration of services

We are developing a Markov Chain model for service migration

Looking at caching content as well

We now move on to the final part of this talk

– Seamless communication in VANETs


VANETs

VANETs are important because they are the key components for building an Intelligent Transportation Infrastructure (ITS)

– ITS involves the integration of the Communication and Transport Infrastructure

Improve safety on the road

– Crash Avoidance, Accident Notification

Infotainment in vehicles

ITS is part of Smart Cities research


VANET Infrastructure

VANET Hardware

– Roadside Units (RSUs)

– Onboard Units (OBUs)

V2I communication

– RSU ↔ OBU (Middlesex University)

V2V communication

– OBU ↔ OBU (USP)

Beaconing V2I or V2V


Seamless V2I

The work of PhD student Arindam Ghosh

How do you guarantee seamless communication between the car and the infrastructure

Seamless handover situation but slightly different

– Velocities may be high

– Beaconing effect• Frequency and size of beacon

Interested in proactive handover


Our Approach is to look at 3 phases of Communication

Data Exchange Phase

– Not concerned about handover

– Can only see 1 RSU

Doing calculation for handover

– Determining Exit Time to start handover

Doing the Handover

All must be done before I leave the first network, i.e., before NDT expires


Scenario


Use Y-Comm Approach to Calculate NDT

A good approximate for NDT is

– NDT ~ 2R/v• R = Radius of coverage of RSU

• V = velocity of the vehicle.

This is an ideal NDT because it is only based on coverage, it assumes no interference between RSU and RSU or OBU and OBU

Measure NDT using simulation and find out how close we get to the ideal NDT and how this result is affected by other factors


Simulation Scenario


Results show that:

The higher the beaconing frequency the greater the NDT from 1Hz ->10 Hz

The size of the beacon also affects the measured NDT

Velocity also affects NDT severely. The greater the velocity the less NDT is available.

Also measured the effect of velocity on data-transfer rates (non-linear)


Data Exchange Rates at Different Speeds


Summary

VANET is a new area for us

Using NDT is a new appoach

Interesting results

Hoping to develop an analytical model

Need to consider other factors

– Traffic density, interference, etc.


Joining the RevolutionJoin a work that has just started

•Hybrid QoS Internet Model

• IEEE 802.21 implementation

• Proactive Channel Allocation

• VANET

Or explore a total new area in Y-Comm

• Programmable Networking

• SDN and Open Flow

• ICN


THANKS FOR LISTENING

ANY QUESTIONS?

NOVEMBER 2013

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