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G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks

G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks. Bin Wang and Sandeep K. S. Gupta Computer Science and Engineering Department Arizona State University Tempe, AZ, USA {Bin.Wang,Sandeep.Gupta}@asu.edu. Outline. Problem Statement Challenges

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G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks

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  1. G-REMiT: An Algorithm for Building Energy Efficient Multicast Trees in Wireless Ad Hoc Networks Bin Wang and Sandeep K. S. Gupta Computer Science and Engineering Department Arizona State University Tempe, AZ, USA {Bin.Wang,Sandeep.Gupta}@asu.edu

  2. Outline • Problem Statement • Challenges • Background and Related Work • System Model & Assumptions • Node’s Energy Consumption Metric • G-REMiT Algorithm & Performance Results • Conclusions

  3. Problem Statement • Given a set of nodes with • wireless transceiver and • power control ability • Find • a group-shared multicast tree such that the total energy consumption of all the nodes is minimized

  4. Difference of Wired & Wireless Network Wired Network Graph Wireless Network Graph

  5. Challenges • Transmission Power determines • The total amount of energy consumed on the link • Feasible of the link • Network topology

  6. Background and Current State of Art • Multicasting • What is? • Allow one entity to communicate efficiently with multiple entities residing in a subset of the nodes in the network • Why multi-destination delivery in a single message? • Transparency; Efficiency; Concurrency • Applications (e.g, distributed database, distributed games, teleconferencing)

  7. Background and Current State of Art Wireless Multicast Advantage

  8. Background and Current State of Art • Building energy-efficient broadcast/ multicast tree • Optimal solution is NP-hard problem [Li LCN2001], heuristic algorithm is needed • Distributed Solution vs. Centralized Solution • High overhead to obtain global knowledge • Dynamic of wireless link and data traffic

  9. Background and Current State of Art • Current heuristic algorithms for building energy efficient broadcast/multicast tree • Minimize cost metric increment for adding a node in the source-based tree. • Using cost metric with energy cost (BIP/MIP, BLU/MLU, BLiMST/MLiMST [Wieselthier Infocom2000]); Dist-BIP-A, Dist-BIP-G [Wieselthier Milcom2002] • Refine a minimum spanning tree (MST) by cover as more downstream node as possible in source-based tree • EWMA, Dist-EWMA [Cagalj Mobicom2002]

  10. System Model & Assumptions • Static Wireless Ad hoc Network • Each node knows the distance between itself and its neighbor nodes • Every node knows the number of nodes in the multicast group • Group message generation rate (in term of bit/s) at every node follow Poisson distribution. And all of these message generation rates are independent random variables

  11. where is energy cost of transmission processing, is Euclidean distance between i and j,  is propagation loss exponent, K is a constant dependent upon the antenna. Wireless Communication Model • The minimum power needed for link between nodes i and j for a packet transmission is: • For short range radio, [Feeney Infocom2001] So is not negligible

  12. Node’s Energy consumption in different multicast sessions

  13. A Group-shared Tree Example

  14. Node’s energy cost metric in Group-shared Tree) • Energy consumed at node i is • If we introduce , then • Node’s Relative Energy Cost Metric

  15. G-REMiT Algorithm • Idea: a node changes its connected tree neighbor to minimize the total energy consumption of tree.

  16. has the largest positive value. So node 2 select node 6 as its new connection tree neighbor. And make . Example of Refinement at a node for minimizing energy consumption of the Tree

  17. R10 may be affected by , because may be changed. Tree’s Energy Consumption Oscillation Avoidance • Lemma 1 : Nodes that are on tree pathj,i are the only nodes in the multicast tree that may be affected by Changeix,j

  18. Disconnection Refinement • Lemma 2: If i is not on tree pathj,x the tree remains connected after Changeix,j

  19. G-REMiT Algorithm Description • Two phases (Core-Based Tree) • First Phase: using distributed algorithm to build MST [Gallager TPLS1983]. • Second Phase: organized by rounds. Each round is leaded by the core node. It terminates G-REMiT algorithm where there is no gains by switching any node in the multicast tree. • In each round, a depth-first search algorithm is used to pass G-REMiT token to the nodes one by one.

  20. Second Phase of G-REMiT

  21. Performance Results Normalized TPC when 50% nodes are multicast group nodes

  22. Performance Results (Cont.) Normalized TPC for a graph with 100 nodes

  23. Conclusions • Energy consumption metric for evaluating energy-efficiency of multicast protocol in WANET • G-REMiT is a distributed algorithm to construct an energy-efficient multicast tree. • G-REMiT Perform better than BIP/MIP Dist-BIP-G, and Dist-BIP-A algorithms for long range radios. • All of the algorithms have similar performance for short range radios.

  24. Future Work • Energy efficient multicast in mobile ad hoc network • Multicast tree lifetime extension • Other schemes for energy efficient multicast of short range radios • Directional antenna • Scheduling sleep mode among the nodes

  25. Reference [1] J.E. Wieselthier, G.D. Nguyen, and A. Ephremides. On the construction of energy-efficient broadcast and multicast tree in wireless networks. In Proceedings of the IEEE INFOCOM 2000, pages 585–594, Tel Aviv, ISRAEL, March 2000. [2] J. E. Wieselthier, G. D. Nguyen, and A. Ephremides, Distributed algorithms for energy-efficient broadcasting in ad hoc networks, Proceedings of MilCom, Anaheim, CA, Oct. 2002. [3] M. Cagalj, J.P. Hubaux, and C. Enz. Minimum-energy broadcast in All-wireless networks: NP-completeness and distribution issues. In Proceedings of ACM MobiCom 2002, pages 172 – 182,Atlanta, Georgia, September 2002. [4] F. Li and I. Nikolaidis. On minimum-energy broadcasting in all-wireless networks. In Proceedings of the 26th Annual IEEE Conference on Local Computer Networks (LCN 2001), pages 193–202, Tampa, Florida, November 2001. [5] R.G. Gallager, P. A. Humblet, and P. M. Spira. A distributed algorithm for minimum weight spanning trees. ACM Transactions on Programming Languages and Systems, 5(1):66–77, January 1983. [6] L. M. Feeney and M. Nilsson. Investigating the energy consumption of a wireless network interface in an ad hoc networking environment. In Proceedings of IEEE INFOCOM, Anchorage, pages 1548 –1557, AK, April 2001.

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