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
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Introduction
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For the purpose of saving power energy consumed in data
communication,
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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.
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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
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Does that g really work?
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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
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G slows down the move of each node.
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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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Our Work
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G works for the cases when the
overreaction occurs frequently (>70%)
in algorithm 1 (MC1).
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Our Work
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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.
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Our Work
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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
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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
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[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.
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