1. Bin Wang, Arizona State Univ S-REMiT: A Distributed Algorithm for Source-based Energy Efficient Multicasting 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. Bin Wang, Arizona State Univ Outline Multicasting in Wireless Network Node Metric Problem Statement S-REMiT Algorithm Related Work Performance Results Conclusions

3. Bin Wang, Arizona State Univ Multicasting Allow one entity to send messages to multiple entities residing in a subset of the nodes in the network Why multi-destination delivery in a single message? –Transparency; Efficiency; Concurrency Applications –distributed database, distributed games, teleconferencing

4. Bin Wang, Arizona State Univ Why Multicasting is different in Wireless Networks? Wireless medium is broadcast medium (Wireless multicast Advantage) –One time local transmission can possibly reach all the neighbors

5. Bin Wang, Arizona State Univ Power control allows a node to determine who are its neighbors. More power used  –more interference –Reduces # simultaneous transmissions (thrput) –Consumes energy at a faster rate  node can die faster leading to disconnections. Why Multicasting is different in wireless network?

6. Bin Wang, Arizona State Univ Why Not Single-Hop Multicast? Single source multicast: reach a subset of nodes from a given source s –s increases its transmission range to such an extent that it can reach all the group members Increased interference and power wastage source may have limited transmission range

7. Bin Wang, Arizona State Univ Multi-hop Approach Multi-hop Solution  Problem of constructing multicast tree 1.What is a link? Depends on power level Using maximum transmission power results in too many links 2.link weight? 1. & 2.  Link-based view not appropriate! –Node-based view: construct tree with “minimum/maximum summation of node cost”

8. Bin Wang, Arizona State Univ Node’s Energy Cost Energy consumed (per bit) at node i in a node s’s Source-based Tree T where and are energy cost (per bit) of transmission processing and reception processing, is length of the link between node i and i’s farthest children.  is propagation loss exponent, K is a constant dependent upon the antenna.

9. Bin Wang, Arizona State Univ Energy Cost of Multicast Tree The Total Energy Cost (TEC) of a multicast tree T : The minimum TEC multicast tree T * is: where T G is the set of all possible multicast trees for the multicast group G in a given graph o. Minimizing TEC of multicast tree  minimizing the energy cost of every tree node as much as possible

10. Bin Wang, Arizona State Univ REMiT Approach Refinement-based- (Take an initial solution and make it better) ? –Needed anyways because of dynamic changes in the network interference Distributed? –Sensor networks may have millions of nodes –High overhead to obtain global knowledge

11. Bin Wang, Arizona State Univ Challenges to Distributed Tree Construction? NP-complete problem [Li, LCN2001], heuristic algorithm is needed How to distribute the computation?

12. Bin Wang, Arizona State Univ Refinement Operation: Change Decrease TEC of the multicast tree by moving node x’s farthest child (say node i) to another node (say node j)

13. Bin Wang, Arizona State Univ Refinement Criterion

14. Bin Wang, Arizona State Univ Oscillation & Disconnection Avoidance Lemma 1: Nodes j and x are the only nodes in the multicast tree whose energy cost may be affected by. Lemma 2: If j is not a descendant of node i in tree T, then the tree remains connected after.

15. Bin Wang, Arizona State Univ S-REMiT Algorithm Two phases –First Phase: Build a MST [Gallager, TPLS1983], or SSSPT [Chandy, ACM1982]. –Second Phase: Using Token passing to guarantee consistency. –Token passing Tree (Initial Tree built in first phase) –Multicast Tree 1.Node s initiates Token passing 2.Once gets the Token, node i selects the new parent for itself with the highest energy gain, say node j. If the highest energy gain is not positive, then pass Token to next ho, otherwise go to Step 3. 3.Node i changes its parent from x to j, then pass Token to next hop. (Node x may pruned if its tree degree = 1 and it is not in the group.) 4.Terminate S-REMiT when there does not exist any positive energy gain.

16. Bin Wang, Arizona State Univ Example of S-REMiT Algorithm 1 2 3 4 Initial MST 3 1)Starts token passing …. 2)Node 4 gets the Token. Moving 4 to node 3 results in the the highest positive energy gain. 3)Node 4 changes its parent from node 2 to 3. …. 4)There exists energy gain in this round, Continue token passing. …. 5)Node 4 gets Token. Moving node 4 to node 1 results in the highest lifetime gain, however, gain is negative. 6)Terminate 1 2 4 S-REMiT Tree

17. Bin Wang, Arizona State Univ Related Work BIP/MIP [Wieselthier, CN2002]); Dist-BIP-A, Dist-BIP-G [Wieselthier, Milcom2002]: adding nodes in the tree one by one with minimum energy increasement. –Limitations: Performance depends on the order of adding nodes in the tree. View is limited by adding one node at one time. 12 3 12 3 2 pJ/bit 3 pJ/bit 2 pJ/bit TEC = 4 pJ/bitTEC = 3 pJ/bit

18. Bin Wang, Arizona State Univ Related Work EWMA, Dist-EWMA[Cagalij, Mobicom2002]: refine MST by allowing upstream nodes cover downstream as much as possible. –Limitations: Greed nature does not fit for multicast tree. 1 2 3 4 8 pJ/bit 2 pJ/bit 7 pJ/bit 2 2 pJ/bit 1 4 TEC = 8 pJ/bit TEC = 6 pJ/bit 3 4 pJ/bit

19. Bin Wang, Arizona State Univ Performance Results

20. Bin Wang, Arizona State Univ Performance Results

21. Bin Wang, Arizona State Univ Performance Results

22. Bin Wang, Arizona State Univ Performance Results

23. Bin Wang, Arizona State Univ Conclusions S-REMiT is a distributed algorithm to conserve energy of source-based multicast tree. S-REMiT performs better than BIP/MIP, EWMA-Dist algorithms.

24. Bin Wang, Arizona State Univ Future Work Other schemes for minimizing energy consumption of multicast tree –Directional antenna –Scheduling sleep mode among the nodes Delay constraint and reliability

25. Bin Wang, Arizona State Univ Reference [1] J. E. Wieselthier, G. D. Nguyen, and A. Ephremides, Resource management in energy-limited, bandwidth-limited, transceiver-limited wireless networks for session-based multicasting. Computer Networks, 39(2):113–131, 2002. [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] B. Wang and S. K. S. Gupta. S-REMiT: An algorithm for enhancing energy-efficiency of multicast trees in wireless ad hoc networks. In Proceedings of IEEE GlobleCOM, San Francisco, CA, Dec. 2003. [7] K. Chandy and J. Misra, “Distributed computation on graphs: Shortest path algorithms,” Communications of the ACM, vol. 25, no. 11, pp. 833–837, Nov. 1982.