On Reducing the Moving Distance in Approaching Optimal Configuration in MANETs

1. On Reducing the Moving Distance in Approaching Optimal Configuration in MANETs Muddana Roopa, Akasapu Girish, Zhen Jiang Computer Science Department West Chester University West Chester, PA 19383 {rm647321|ga642467|zjiang}@wcupa.edu Mobiquitous'07 Poster

2. Introduction • For the purpose of saving power energy consumed in data communication, • The optimal positions of the relay nodes along the single active flow must lie entirely on the line between the source and the destination, with each node spaced evenly along such a line [1]. • To move each relay node to its optimal position while keeping its connection with the neighbors along the path of data flow, a distributed averaging algorithm [2,3] can be used to adjust the node position. • Assume that all the nodes in MANETs have the same communication range. • Assume a data flow path has been discovered using a routing protocol • Algorithm 1 [1]: Every node is required to compute the average of its two neighbors and then move to that new position. • Algorithm 2 [4]: Every node maintains the location information of its neighbors. By one extra round of information exchange, the 2-hop neighborhood is collected and used in the above averaging process. Mobiquitous'07 Poster

3. Introduction Algorithm 1 Algorithm 2 Mobiquitous'07 Poster

4. Introduction • In [1], to reduce the effect of overreaction, dumping factor g(0,1] is set for each move. As a result, a node moves towards the new position, instead of reaching that. The move wasted in overreaction can be saved. Therefore, the moving distance and the energy consumed in node mobility can be reduced. Mobiquitous'07 Poster

5. Problem • Does that g really work? • Does g work for any case of averaging algorithm in reducing total moving of a relay node? • How much the reduction of node moving can this g bring to us? Mobiquitous'07 Poster

6. Our Work • G slows down the move of each node. • More time is needed to reach the optimal position. • The total moving is not reduced a lot. • See the simulation at: http://www.cs.wcupa.edu/~rkline/mobility/mobilityplot3.html • An example is shown as the follows. Mobiquitous'07 Poster

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8. Our Work • G works for the cases when the overreaction occurs frequently (>70%) in algorithm 1 (MC1).

9. Our Work • G DOES reduce the node moving distance in the cases when the rate of the occurrence of overreaction is low (<30%), including the cases in Algorithm 2. • But g INCREASEs the time needed.

10. Our Work • When lagged (by one round) information is used in algorithm 2, g not only slows down the converging of averaging process, but also increases the total moving distance.

11. Conclusion • The use of g is to lag the move of node. • If lagged location information or incorrect location information is used, the use of g DOES not help our mobility control for achieving optimal configuration. • In the case when the rate of the occurrence of overreaction is low, the use of g will slow down the converging of averaging process and cause more energy consumption when the configuration is used by communication during the averaging process. • Future work: a more efficient moving control is under development. Mobiquitous'07 Poster

12. References • [1] D. Goldenberg, J. Lin, A. Morse, B. Rosen, and Y. Yang. “Towards Mobility as a Network Control Primitive”. Proc. of Mobihoc’04. May 2004, pp. 163-174. • [2] A. Jadbabaie, J. Lin, and A. Morse. “Coordination of Group of Autonomous Mobile Agents using Nearest Neighbor Rules”. IEEE Transactions on Automatic Control, 48(6), 2003, pp. 988-1001. • [3] A. Rao, C. Papadimitriou, S. Shenker, and I. Stoica. “Geographic Routing without Location Information”. Proc. of Mobicom’03. Sept. 2003, pp. 96-108. • [4] Z. Jiang, J. Wu, and R. Kline. “Localized Mobility Control with inconsistent Views of Neighborhood in Mobile Networks”. IEEE NAS’06, August 2006. Thank you! Mobiquitous'07 Poster