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

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 Wireless Communication Model The minimum power needed for link between nodes i and j for a packet transmission is: So is not negligible For short range radio, 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. [ Feeney Infocom2001 ]

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

17 Tree’s Energy Consumption Oscillation Avoidance R 10 may be affected by, because may be changed. Lemma 1 : Nodes that are on tree path j,i are the only nodes in the multicast tree that may be affected by Change i x,j

18 Disconnection Refinement Lemma 2: If i is not on tree path j,x the tree remains connected after Change i x,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 [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 [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 [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 [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 [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.