on reducing the moving distance in approaching optimal configuration in manets

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On Reducing the Moving Distance in Approaching Optimal Configuration in MANETs

Muddana Roopa, Akasapu Girish, Zhen JiangComputer Science Department

West Chester UniversityWest Chester, PA 19383

{rm647321|ga642467|zjiang}@wcupa.edu

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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.

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Introduction

Algorithm 1

Algorithm 2

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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.

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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?

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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.

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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.

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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.

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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.