Click here to load reader
Upload
naoki-shibata
View
1.737
Download
2
Tags:
Embed Size (px)
DESCRIPTION
Takashima, E., Murata, Y., Shibata, N., Yasumoto, K. and Ito, M.: A Method for Distributed Computaion of Semi-Optimal Multicast Tree in MANET, IEEE Wireless Communications and Networking Conference (WCNC 2007), pp. 2570-2575, DOI:10.1109/WCNC.2007.478 (March 2007). http://ito-lab.naist.jp/themes/pdffiles/070314.eiichi-t.wcnc2007.pdf In this paper, we propose a new method to construct a semi-optimal QoS-aware multicast tree on MANET using distributed computation of the tree based on Genetic Algorithm (GA). This tree is sub-optimal for a given objective (e.g., communication stability and power consumption), and satisfies given QoS constraints for bandwidth and delay. In order to increase scalability, our proposed method first divides the whole MANET to multiple clusters, and computes a tree for each cluster and a tree connecting all clusters. Each tree is computed by GA in some nodes selected in the corresponding cluster. Through experiments using network simulator, we confirmed that our method outperforms existing on-demand multicast routing protocol in some useful objectives.
Citation preview
2.
Outline of this presentation 3. Background
4. Background
5. Existing studies
[2] Li Layuan and Li Chunlin, "QoS Multicast Routing in Networks with Uncertain Parameters", APWeb, (2003). [1] P. Sinha and R. Sivakumar and V. Bharghavan, "MCEDAR: Multicast core extraction distributed ad-hoc routing", WCNC(1999), 6.
Outline of this presentation 7. Goal of this research
8. Our Approach
9. Hierarchical computation
cluster Global Tree node Local tree 10. Target Environment & Assumption
11. Problem Definition
12. Typical Objective Functions
Term for power consumption can also be added service availability Tree stability service availability Tree stability 13. ProcedurePhase1: Cluster division Cluster division Gathering topology infoin each cluster Gathering topology infobetween clusters Computation of global tree Cluster re-division Computationof local tree Inter cluster e e e e e S Intra cluster Cluster head: responsible to local tree construction Top cluster head: responsible to global tree construction e e e e e S 14. Phase2:Gathering Local Topology Info Cluster division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division Inter cluster Intra cluster (1) Cluster head floods request msg in its cluster e e e e e S Computation of global tree Computationof local tree e e e e e S 15. Phase2:Gathering local topology Info Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division Inter cluster Intra cluster (1) Cluster head floods request msg in its cluster(2) Each nodereceived the message sends back a message with its ID and link state info including B/W and delay to neighboring nodes. e e e e e S Computation of global tree Computationof local tree e e e e e S 16. Phase3:Gathering global topology info Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division Inter cluster e e e e e S (1) Each cluster head measures QoS info on paths to cluster heads of adjacent clusters. (2) Each cluster head sends the info to the top cluster head. Intra cluster Computation of global tree Computationof local tree e e e e e S 17. Phase4: Computation of global tree Inter cluster Intra cluster e e e e e S Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division (1) Top cluster head (and some nodes) computes global tree by using island model GA. Computation of global tree Computationof local tree e e e e e S 18. Phase4: Computation of global tree Inter cluster Intra cluster Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division (1) Top cluster head (and some nodes) computes global tree by using island model GA. (2) Information of global tree is sent to each cluster head in the tree. Computation of global tree Computationof local tree e e e e e S e e e e e S 19. Phase5: Computation of local tree Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division Inter cluster e e e e e S Intra cluster Each cluster head computes local tree which can be grafted to global tree Computation of global tree Computationof local tree e e e e e S 20. Phase5: Computation of local tree Inter cluster Intra cluster Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division The island model GA is used for computation of local tree Computation of global tree Computationof local tree e e e e e S e e e e e S 21. Phase5: Computation of local tree Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division Inter cluster e e e e e S Intra cluster Computation of global tree Computationof local tree The info of local tree is sent to each node in the tree e e e e e S 22. Phase5: Computation of local tree Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division Inter cluster e e e e e S Intra cluster Computation of global tree Computationof local tree The semi-optimal multicast tree has been constructed among nodes. e e e e e S 23. Phase6: Cluster re-division Cluster Division Gathering topology infoin each cluster Gathering topology infobetween clusters Cluster re-division Inter cluster e e e e e S Intra cluster Computation of global tree Computationof local tree After a while, MANET is clustered again and procedure from phase2 is repeated to reflectchange of topology. e e e e e S 24.
Outline of this presentation 25. Evaluation
26. Advantage of the proposed algorithm
27. Result of (re)computation time of tree
Seconds Computation time approximation of computation time Re-computation time approximation of recomputation time Number of nodes sufficient 28. Feasibility in practical environment
29. Superiority to existing method
30. Comparison with existing method
[3]K. Bur and C. Ersoy. Ad Hoc Quality of Service Multicast Routing.Computer Communications , 29(1):136148, December 2005. Power saving stability number of receivers Yes No Yes Power-saving No No Yes #. of receivers No Yes Yes Stability 31. Transition of packet arrival rate The proposed method issuperiorto AQM in terms of packet arrival rate second AQM Stability #. of receivers Power-saving 32. Conclusion
33.
34. Result of power consumption Unit : Watt-second 35. Power consumption