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Universität Stuttgart Institute of Parallel and Distributed Systems (IPVS) Universitätsstraße 38 D-70569 Stuttgart Evaluation of Partition-Aware MANET.

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Presentation on theme: "Universität Stuttgart Institute of Parallel and Distributed Systems (IPVS) Universitätsstraße 38 D-70569 Stuttgart Evaluation of Partition-Aware MANET."— Presentation transcript:

1 Universität Stuttgart Institute of Parallel and Distributed Systems (IPVS) Universitätsstraße 38 D Stuttgart Evaluation of Partition-Aware MANET Protocols and Applications with ns-2 A. Khelil, P.J. Marrón, R. Dietrich, K. Rothermel

2 Universität Stuttgart IPVS Research Group “Distributed Systems” 2 Motivation Recent research*: network partitioning is very frequent in MANETs Network partitioning complicates ◦ Routing, broadcasting, multicasting ◦ Data management: aggregation, querying, consistency  Recent protocols and applications (have to) consider partitioning Developers need to evaluate their partition-aware concepts ◦ By comparing them to the optimal case ◦ Using partitioning metrics The widely used simulator ns-2 does not provide support for evaluation of partition-aware protocols and applications *) J. Haehner et al. “A Quantitative Analysis of Partitioning in MANETs” Sigmetrics, 2004.

3 Universität Stuttgart IPVS Research Group “Distributed Systems” 3 Outline Motivation Providing Partitioning Information for ns-2 ◦ Annotation tool ◦ Extension of ns-2 Case Study: A Partition-Aware Broadcast Protocol Conclusion

4 Universität Stuttgart IPVS Research Group “Distributed Systems” 4 The Network Simulator ns-2 Ns-2 is ◦ A discrete event simulator for wired & wireless networks ◦ Widely used ◦ Implemented ▪ C++ (for data manipulation and protocol implementation) ▪ OTcl (for configuration) General Operations Director (GOD): central instance ◦ Stores global state information (#nodes, node position,..) ◦ Stores an array of the smallest number of hops between 2 nodes (optimal routing information)

5 Universität Stuttgart IPVS Research Group “Distributed Systems” 5 Annotation Tool General Operations Director (GOD) Partition-AwareProtocolEvaluation Query() Subscribe() Partitioning information ns-2 Simulationtrace Arbitrary ns-2 movement trace Before simulation During simulation Movement trace annotated with partitioning information Approach: Providing Partitioning Information for ns-2 Basic communication model A and B communicate if distance(A,B) <= comm_range

6 Universität Stuttgart IPVS Research Group “Distributed Systems” 6 Query Interface A Protocol agent A GOD C B Query() Packet P1 recv() { … query() … } *) J. Haehner et al. “A Quantitative Analysis of Partitioning in MANETs” Sigmetrics, query(): 1) Current partitioning situation: - getNumberOfPartitions() - getNodesOfPartition() - … 2) Statistics: - getNumberOfJoins(t1,t2) - getNumberOfSplits(t1,t2) - … 3) Partitioning metrics defined in *) - getAvgNumberOfPartitions(t1,t2) - getAvgPartitionSize(t1,t2) - getPartitionChangeRate (t1,t2) - …

7 Universität Stuttgart IPVS Research Group “Distributed Systems” 7 Subscribe Interface A Protocol agent A GOD C B Partitions: {A,B,C} call-back() subscribe()

8 Universität Stuttgart IPVS Research Group “Distributed Systems” 8 We provide to ns-2 community ◦ Annotation tool ◦ Patch for ns-2 extension Tested Environments: ◦ Ns-2: 2.1b9a, 2.26, 2.27, 2.28 ◦ OS: Linux, Solaris

9 Universität Stuttgart IPVS Research Group “Distributed Systems” 9 Outline Motivation Providing Partitioning Information for ns-2 Case Study ◦ A partition-aware broadcast protocol: hypergossiping ◦ Evaluation approaches ◦ Simulation results Conclusion

10 Universität Stuttgart IPVS Research Group “Distributed Systems” 10 Hypergossiping combines two strategies ◦ Gossiping for intra-partition forwarding ◦ Broadcast repetition ▪ Partition join detection heuristic ▪ Rebroadcast The Protocol: Hyper-Gossiping (HG)  Partition joins are critical for hypergossiping  Detection from both directions needed

11 Universität Stuttgart IPVS Research Group “Distributed Systems” 11 Evaluation of Hypergossiping Performance metrics for hypergossiping ◦ Reachability: ◦ Message overhead ◦ Delay Evaluation of the broadcast repetition ◦ Gain metric (used for calibration): ◦ Comparison of performance metrics to that of the optimal case (  approach 1) ◦ Observe protocol decisions (  approach 2) Needed global views ◦ Partitioning global view (provided by GOD) ◦ Broadcast global view (= which packet has reached which node)

12 Universität Stuttgart IPVS Research Group “Distributed Systems” 12 Optimal broadcast repetition: ◦ Optimal join detection (partition global view provided by GOD) ◦ Optimal rebroadcasting: determine the packets that have to be rebroadcasted (broadcast global view) Two simulation runs needed ns-2 HGHG HG with Optimal Broadcast Repetition (OBR) HG with Optimal Broadcast Repetition (OBR) Partition global view Partition BroadcastglobalviewBroadcastglobalview HG reachability HG message overhead HG delay HG(OBR) reachability HG(OBR) message overhead HG(OBR) delay AnnotatedmovementtraceAnnotatedmovementtrace Evaluation Approach 1: Optimal Case

13 Universität Stuttgart IPVS Research Group “Distributed Systems” 13 Comparison to the Optimal Reachability Quantification of improvement potentials for reachability Distance to optimal case simplifies the design of hypergossiping ◦ Finding critical scenarios ◦ tuning algorithm parameters

14 Universität Stuttgart IPVS Research Group “Distributed Systems” 14 Observer evaluates each decision of the join detection heuristic One simulation run needed AnnotatedmovementtraceAnnotatedmovementtrace ns-2 HGHG HG Observer PartitionglobalviewPartitionglobalviewBroadcastglobalviewBroadcastglobalview Join detections by HG heuristic correctwrongredundant Evaluation Approach 2: Observer

15 Universität Stuttgart IPVS Research Group “Distributed Systems” 15 Observing Join Detections Number of joins is easily provided by GOD Quantification of improvement potentials of our join detection heuristic The suppression mechanism of HG works well, since number of redundant detections is very low

16 Universität Stuttgart IPVS Research Group “Distributed Systems” 16 Conclusion Our extension to ns-2 allows ◦ easy access to valuable network partitioning information ▪ easy definition of optimal case ▪ detailed observation of protocol decisions Annotation tool ◦ Time-complexity of annotation is comparable with that of setdest, the random waypoint trace generator of ns-2 ◦ Next steps: support other communication models

17 Universität Stuttgart Institute of Parallel and Distributed Systems (IPVS) Universitätsstraße 38 D Stuttgart Thank you for your attention!http://canu.informatik.uni-stuttgart.de/calcpartition


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