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Performance of group communications over adhoc networks

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Prob exactly one arrival = l Dt ... Initial conditions: anything reasonable for mZ(0), such as zero or m0. Only m Z is differential. ... – PowerPoint PPT presentation

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Title: Performance of group communications over adhoc networks


1
Performance of group communications over ad-hoc
networks
  • Marc Mosko and J.J. Garcia-Luna-Aceves
  • Department of Computer Engineering
  • U.C. Santa Cruz
  • ISCC 2002
  • Sicily, July 1-4 2002

2
Presentation Outline
  • Goals motivation
  • Overview of model
  • Comparison to simulation
  • Further research
  • Conclusion

3
Goals Motivation
  • Goals
  • Steady-state model of broadcasting in
    contention-based (ALOHA) ad-hoc networks that
    accounts for correlated packet loss due to
    hidden-terminal collisions for reliable (NAKs)
    and unreliable broadcast.
  • Use model to predict performance of ad-hoc
    network using FEC coding for inter-packet erasure
    correction for broadcast/multicast distribution
    (not in present work).

4
Model Introduction
  • Radio Link Layer
  • Common channel radio, no capture, no loss from
    noise
  • May not transmit and receive at same time
  • 802.11 / ALOHA broadcasts (i.e. unreliable)
  • Topology cluster tree formation
  • Nodes grouped in fully connected components
  • Components connected in tree
  • Each component has a single cluster head that is
    in hearing range of parent, repeats for other
    cluster members
  • Subset of other cluster members repeat for other
    components

5
Binary cluster tree
Cluster tree allows Repairs through
siblings. Only allows 1 repair attempt even if
more siblings.
6
Rate-based fluid model
  • Infinitesimal bit rate
  • Model based on rates, not information. No
    queuing.
  • Assume all rates are Poisson (or modulated P.)
  • Total in-bound rate l l1 lk
  • Prob zero arrivals (1-l) Dt
  • Prob exactly one arrival l Dt
  • Out-bound rate in next Dt will be collision-free
    part of in-bound rate in current Dt.

7
Filtering process
  • mi out-bound rate from i
  • ei,z, info density i to z
  • Noise part of m that add no new information
  • needs non-local terms
  • pi,z , prob z hears i
  • pi,z 1 S mk,
  • k ? N(z)z-i
  • li,z, useful rate i to z
  • li,z mi ei,z, pi,z
  • lz S li,z

8
Unreliable Broadcast
  • Source m0 driving rate
  • Difference eq.
  • mZ(tDt)- mZ(t)lZ(t)-mZ(t)Dt
  • Differential eq. (i ? N(z))
  • m?Z(t) -mi(t) S mi ei,z, pi,z
  • Initial conditions anything reasonable for
    mZ(0), such as zero or m0.
  • Only m?Z is differential.
  • mi out-bound rate from i
  • ei,z, info density i to z
  • pi,z , prob z hears i
  • pi,z 1 S mk,
  • k ? N(z)z-i
  • li,z, useful rate i to z
  • li,z mi ei,z, pi,z
  • lz S li,z

9
Reliable broadcast
  • NAK-based, 1 NAK per missed info quanta
  • ??Z(t) lp (t) lz (t) , p parent of z
  • Retransmission rate
  • z?Z(t) -zZ(t) S ?i (t)pi,z (t) , i ? C(z)
  • Problem Should use non-local terms
  • ??Z(t) lp (t-Dt) lz (t)
  • z?Z(t) -zZ(t) S ?i (t -Dt)pi,z (t)
  • l?z(t) also needs them

10
Reliable broadcast equations
  • At source node with driving rate m0
  • m?0 m0 mo z0
  • At other nodes
  • m?z lz mz ?z zz
  • All terms are differentials to be solved each Dt.
  • mi out-bound rate from i
  • ei,z, info density i to z
  • pi,z , prob z hears i
  • li,z, useful rate i to z
  • ?z NAK rate at Z
  • zZ Retrans. rate at Z

11
Comparison to simulation
Unreliable broadcast
Reliable broadcast
12
End-to-end seqno NAKs
  • If you forward out-of-order packets immediately
    (min. delay), you may create nak storms.
  • Snooping limited to 1-hop radius
  • Delays do not work well and if based on hop count
    from source may cause long latency
  • We used per-hop seq. no. in paper, solved
    problem. Better solution would be to use
    forward NAK notification bit in packet to
    indicate it was already NAKed.

13
Future work
  • Consider non-local terms.
  • Validate against other network topologies.
  • Allow multiple repair attempts in cluster, this
    appears to be main problem in larger clusters.
  • Use results in FEC code calculations similar to
    ICNP 2000 work.
  • What rate codes make sense in this environment?
  • Packet lengths packet pacing.

14
Conclusion
  • Classifications terms
  • Definitions of symbols seem to make sense, rate
    equations may be easily read.
  • For binary cluster tree, results are not too bad,
    even without non-local terms.
  • Exposed issue of using end-to-end sequence
    numbers for NAK generation.
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