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

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Supporting the Brave New World of the 4As
Anytime, Anywhere, Anyhow and Anything
Glenford Mapp Associate Professor Middlesex
University United Kingdom
NOVEMBER 2013
WTD-ICMC-USP
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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

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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

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Anyhow

• We 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

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Anything

• Most 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

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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 future
• Proactive approach
• Know where network infrastructure is located
• Privacy of Location Information

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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

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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

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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

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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

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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

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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

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Meeting these challenges

• Need 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

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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

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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

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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

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PERIPHERAL NETWORK
CORE NETWORK
SECURITY LAYERS
APPLICATION ENVIRONMENTS
SERVICE PLATFORM
SAS
QBS
QOS LAYER
NETWORK QOS LAYER
END SYSTEM TRANSPORT
CORE TRANSPORT
NTS
NAS
NETWORK MANAGEMENT
MOBILITY MANAGEMENT
HANDOVER MANAGEMENT
CONFIGURATION LAYER
NETWORK ABSTRACTION (MOBILE NODE)
NETWORK ABSTRACTION (BASE STATION)
HARDWARE PLATFORM (MOBILE NODE)
HARDWARE PLATFORM (BASE STATION)
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A very brief Introduction to Y-Comm

• This is not a talk about Y-Comm
• Talks, papers at http//www.mdx.ac.uk/research/sc
  ience_technology/informatics/projects/ycomm.aspx
• In essence Y-Comm is an architecture that is
  trying to integrate
• Communication
• Mobility
• QoS
• Security

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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

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Why is Y-Comm different

• Y-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

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Future Internet
Current Internet
BACKBONE
ACCESS NETWORKS
WIRELESS NETWORKS
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The Core Framework
SERVICE PLATFORM LAYER
NETWORK QOS LAYER
CORE TRANSPORT SYSTEM
NETWORK MANAGEMENT LAYER
CONFIGURATION LAYER
NETWORK ABSTRACTION LAYER
HARDWARE PLATFORM LAYER
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The Peripheral Framework
APPLICATION ENVIRONMENTS LAYER
QOS LAYER
END TRANSPORT SYSTEM
MOBILITY MANAGEMENT LAYER
HANDOVER MANAGEMENT LAYER
NETWORK ABSTRACTION LAYER
HARDWARE PLATFORM LAYER
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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

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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)

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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)

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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)

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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

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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

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End of Y-Comm Part

• Y-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

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Questions on Y-Comm
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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

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Basic Handover Terms

• Hard 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

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Handover Classification
HANDOVER
ALTERNATIVE
IMPERATIVE
SERVICES
NETPREF
REACTIVE
USERPREF
CONTEXT
PROACTIVE
UNANTICIPATED
ANTICIPATED
MODEL-BASED
KNOWLEDGE-BASED
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Knowledge-Based Proactive Handover (Cambridge)
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Model Based Proactive Handover

• The 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

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Model-Based Handover
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Predictive Mathematical Model for TBVH(Simple
Case)
Movement of MS under BBS coverage (upward
vertical handoff)

• Introduction of additional functionality to Base
  Station at
• network boundary (BBS).
• Distance between MS and BBS derived from location
  
• co-ordinates or
• Estimated TBVH

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Simulation and Results
TBVH simulation in OPNET Modeler
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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?

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Combining Transport and Communications to
determine the optimum handover
NET A
A
NET B
S
NET C
B
C
T
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Analysis shows that it is possible to calculate
these key points with some degree of accuracy
C1
E1
Y2
A
Z1
Y1
Y3
H1
C2
S
B
E2
C
H3
E3
H2
T
Z2
Z3
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Results
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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)

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WIRELESS NETWORK
REQ (Time , TBVH, NDT)
A
A
B
REQ (Time , TBVH, NDT)
B
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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

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There are 3 possible outcomes

• No contention
• (Time TBVH)A lt (Time TBVH)B
• (Time TBVH NDT)A lt (Time TBVH)B
• Contention Two Types Partial and Total
• (Time TBVH)A lt (Time TBVH)B
• (Time TBVH NDT)A gt (Time TBVH)B
• Partial Contention
• Total Contention

(Time TBVH NDT)A lt (Time TBVH NDT)B
(Time TBVH NDT)A gt (Time TBVH NDT)B
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Request Summary

• Requests 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

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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

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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

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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

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The Service Delivery Framework
SERVICE MANAGEMENT LAYER
SERVICE SUBSCRIPTION LAYER
SERVICE DELIVERY LAYER
SERVICE MIGRATION LAYER
SERVICE CONNECTION LAYER
NETWORK ABSTRACTION LAYER
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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

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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

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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

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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

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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

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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

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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

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Scenario
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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

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Simulation Scenario
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Results show that

• The higher the beaconing frequency the greater
  the NDT from 1Hz -gt10 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)

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Data Exchange Rates at Different Speeds
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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.

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Joining the Revolution

• Join 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

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THANKS FOR LISTENING ANY QUESTIONS?
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