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Towards a Science of Networks: Communication Networks I

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Examine communication network theory from different ... Raul J. Mondrag n, Queen Mary, University of London. 31 ... on social insect paradigm (ants) ... – PowerPoint PPT presentation

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Title: Towards a Science of Networks: Communication Networks I


1
Towards a Science of NetworksCommunication
Networks I
  • Report on workshop held at the University of
    Birmingham, UK, 3 4 November 2005
  • (including brief comments on Rome and Budapest
    workshops)
  • Costas Constantinou

2
Workshop aims
  • Examine communication network theory from
    different perspectives physics, engineering and
    computer science
  • Take stock of state of the art
  • Challenge conventional wisdom assumptions for
    network design/operation (strong held opinions
    versus fundamental properties)
  • Define a set of grand challenges to enable the
    creation of a coherent scientific theory of
    networks

3
Some background history
  • Workshop was preceded by a U.S. workshop on the
    complex behaviour of adaptive, network-centric
    systems, hosted by the University of Maryland on
    12 14 July 2005
  • Interdisciplinary aspects of complexity science
  • Applicability to predictable emergent behaviour
    in distributed systems/networks
  • Very strong emphasis on wireless networks

4
Workshop presentations
  • Report on Workshop on the Complex Behaviour of
    Adaptive, Network-Centric Systems Dr. Stuart D.
    Milner, University of Maryland
  • Logical Network Abridgement leading to Diversity
    and Resilience Measures on Networks Dr Costas
    Constantinou, University of Birmingham
  • Spreading Processes on Complex Networks Theory
    and Applications Maziar Nekovee Complexity
    Group, Mobility Research Centre, BT

5
Workshop presentations (cont.)
  • Algorithms and Survivable Protocols for
    Scale-Free and Scale-Free Small World Networks
    András Lörincz, Eötvös Loránd University
  • Information flow issues in cross-layer models of
    wireless communication networks Professor
    Leandros Tassiulas, University of Thessaly
  • MAC-Layer Selfish Behaviour in Wireless Networks
    A Repeated Game Approach Jerzy Konorski, Gdansk
    University of Technology

6
Workshop presentations (cont.)
  • Transmit beamforming strategies for PHY-layer
    multicasting with QoS guarantees Professor Nikos
    Sidiropoulos, Technical university of Crete
    Greece
  • Traffic theory for the Internet and its
    implications on network design Jim Roberts,
    France Telecom
  • Congestion and Centrality Raul J. Mondragón,
    Queen Mary, University of London

7
Workshop presentations (cont.)
  • Physics of networks state of the art José F. F.
    Mendes, University of Aveiro
  • Large-Scale Behaviour of Packet-Switched Networks
    Sanya Stepanenko, University of Birmingham

8
Workshop panel discussions
  • The first panel session concentrated on the
    network properties that need to be predicted
    reliably
  • Conclusion Nearly all observable variables are
    either data rates, such as capacity, throughput,
    loss rate, etc., or delays, such as packet
    transport delay, start-up and recovery times,
    etc., all of which should be predicted
    statistically to estimate their distributions
    correlations, as their mean values are not
    sufficient

9
Workshop panel discussions (cont.)
  • The second panel session attempted to list the
    ingredients for a viable theory of networks
  • Four main components to such a theory
  • Input traffic demand to a network
  • Network topology
  • Routing protocol operation and
  • Interaction between above three components
  • A clean separation of time-scales for the various
    component processes would make the formulation of
    a theory of networks easier, but the discussion
    did not go into establishing whether such a
    separation is applicable

10
Workshop panel discussions (cont.)
  • Conclusion The individual components of a theory
    of networks already exist and are well understood
    in isolation. However, these partial theories
    fall short of an overall theory of networks in
    two ways
  • The interactions between different components
    need to be specified in a unified framework,
    taking particular care to determine the relevant
    time-scales pertinent to the problem under study
  • Even though in principle current formalisms can
    be used to describe networks in all their
    aspects, the number of variables becomes
    intractably large even for modest sized networks

11
Rome Workshop
  • Biologically Inspired Information Systems
    Workshop
  • Held in Rome, 24 26 July 2006
  • Organised by the Università di Roma La Sapienza
  • Funded by ONR

12
Rome Workshop
  • Biologists largely working with neural networks
    (NN)
  • NN nodes are non-linear and have non-linear
    interactions
  • NN are viewed as computation circuits
  • Unlike communication networks coarse-graining is
    meaningless within our current framework of
    understanding
  • Neuroplasticity, i.e. the brain's ability to
    reorganize itself by forming new neural
    connections to compensate for injury and disease
    and to adjust its activities in response to new
    situations or to changes in their environment, is
    an interesting unexplored mechanism that could be
    exploited in self-healing networks

13
Rome Workshop (cont.)
  • Analogies with some biological networks are
    useful
  • Routing based on social insect paradigm (ants)
  • Synchronisation based on coupled oscillators
    (fireflies)
  • Topology management in overlay networks based on
    differential cell adhesion
  • Immune system inspired security
  • Game theory not really biology, but economics
    for emergence of self-organised cooperation

14
Rome Workshop (cont.)
  • General problem is the very restricted range of
    known/predictable emergent behaviour from local
    interaction rules
  • Concept of time/time-scales and their impact on
    dynamics is often based on educated guesswork
  • Strict adherence to biological analogies not
    always sensible should only be used as starting
    point

15
Budapest workshop
  • Social Networks and Complexity Workshop
  • Held in Budapest, 31 July 2 August 2006
  • Organised by the Institute for Advanced Study at
    the Collegium
  • Co-funded by AFOSR and ONR

16
Budapest workshop (cont.)
  • Social scientists are heavily concerned with the
    study of social network structures either that
    of static topologies (e.g. clustering, cliques,
    etc.), or the topology evolution dynamics
  • Theory (random, scale-free and small world graph
    growth process models dominate) eigenvector
    spectrum of connectivity matrix
  • Numerical simulations (node/link
    decimation/addition, percolation thresholds)
  • Measurements

17
Budapest workshop (cont.)
  • Simple coupled dynamical process node models
    (agents as local dynamical processes often
    based on Game Theory)
  • Co-clustering of overlay processes on network
    topology using bi-partite graphs A bipartite
    network can be used as a (general) mapping
    between two interacting networked processes
  • Smallpox epidemic dynamics (not social networks)
    has strong similarities to mobile ad hoc networks
  • Many social networks tend to be networks in a
    not very precise sense

18
Common problems across disciplines
  • Topology and overlay processes are both dynamic
    but often on different time scales
  • Layering of processes (more than one overlays)
  • The predictable mapping local interaction
    behaviours to emergent global observable
    properties is poorly understood
  • Not enough effort goes towards identifying
    differences as opposed to similarities (not
    everything is scale-free symptom)

19
Common problems across disciplines (cont.)
  • Identifying and modelling the sources of
    stochasticity is often incompletely done
  • Too many types of topology classification
    (taxonomy), but no fundamental understanding of
    topology groups/types
  • No identified order parameters for emergent
    properties conversely we know nothing about
    invariants

20
Differences between disciplines
  • Exaggerated view
  • Communications
  • Data flow networks
  • Routing process
  • Biology
  • Neural networks
  • Topology re-construction and pattern
    identification
  • Social sciences
  • Agent networks
  • Static topology analysis

21
State of the art?
  • All three disciplines are currently posing
    problems
  • New problems that arise could lead to a
    convergence in the posing of the fundamental
    problems in network science
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