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Meeyoung Cha and DK Lee Advisor - Sue Moon (Korea Advanced Institute of Science and Technology)

Split-n-Save : Path Multiplexing in Wireless Ad Hoc Routing. Meeyoung Cha and DK Lee Advisor - Sue Moon (Korea Advanced Institute of Science and Technology). IEEE INFOCOM 2005 Student Workshop. Motivation of Our Work.

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Meeyoung Cha and DK Lee Advisor - Sue Moon (Korea Advanced Institute of Science and Technology)

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  1. Split-n-Save :Path Multiplexing in Wireless Ad Hoc Routing Meeyoung Cha and DK Lee Advisor - Sue Moon (Korea Advanced Institute of Science and Technology) IEEE INFOCOM 2005 Student Workshop

  2. Motivation of Our Work • On-demand routing is favored in resource constrained environments of wireless ad hoc network.(e.g., AODV, DSR) • Recent routing schemes use multipath routing for fast path fail-over. (e.g., AOMDV, MDSR, NDMR, MP-DSR, SMR) Do existing multipath routings perform well in terms of the number of active nodes over a time period or workload balancing throughout the network? “ ”

  3. Multipath Routing Basics Description of a typical multipath routing 1. using default path Destination 2. failure detection X 3. fast transition to one of the candidate paths default path Origin candidate paths 4. using new path Candidate paths are used only after the main path is no longer available. Let’s use multiple paths more actively!

  4. Split-n-Save • We propose Split-n-Save • Added featureto an existing multipath routing protocol (patch to AOMDV ns-2 code) • Use path multiplexing change paths every k (frequency of multiplexing) packets Expectedbenefits of Split-n-Save • Inherit all benefits from the underlying routing protocol • Improve routing performance • number of active nodes over a time period • well-balanced workload throughout the network

  5. Routing Performance Metrics • To measure the efficacy, we use the following metrics. • Packet delivery ratio • Average end-to-end delay • Routing overhead We also propose using two other metrics. • Node satisfiability : ratio of the number of forwarding packets generated by itself and that by the other nodes • Network survivability : number of active nodes over a period of time

  6. Simulation Settings • CMU wireless extensions to ns-2

  7. Simulation There exists a specific k value that performs best for each routing performance metric.

  8. Simulation – End-to-end Delay surging points We find several surging points when k = 0 and 1.

  9. Simulation – Node Satisfiability node satisfiability # of packets sent by itself # of packet forwarded = Node satisfiability improves when k > 0.

  10. Preliminary Results • For network survivability, temporal information alone was not enough. We plan to use spatial info as well. - track down the location and causality of node failure. • For other metrics, path multiplexing clearly improves the routing performance with carefully chosen frequency of multiplexing.

  11. Conclusions • We propose and evaluate Split-n-Save, which exploits path multiplexing in multipath routing. • We propose two other metrics: • node satisfiability and network survivability • Frequency of multiplexing can be used to cope with path fail prediction and path optimality. • Path multiplexing should reflect network dynamics.

  12. Future Works • Methodology • Probabilistic model for Split-n-Save • Other multiplexing idea • Revisit routing performance metrics for wireless ad hoc network • Suggestions on simulation in wireless ad hoc network • Good guideline for simulation setups • More practical movement pattern model • Grid movement, communication on the road, campus network

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