PSO-Optimized Hopfield Neural Network-Based Multipath Routing for Mobile Ad-hoc Networks

DOI

10.1080/18756891.2012.696921How to use a DOI?

Keywords

Mobile ad-hoc networks, Reliability, Multipath routing, Neural networks, Particle swarm optimization (PSO)

Abstract

Mobile ad-hoc network (MANET) is a dynamic collection of mobile computers without the need for any existing infrastructure. Nodes in a MANET act as hosts and routers. Designing of robust routing algorithms for MANETs is a challenging task. Disjoint multipath routing protocols address this problem and increase the reliability, security and lifetime of network. However, selecting an optimal multipath is an NP-complete problem. In this paper, Hopfield neural network (HNN) which its parameters are optimized by particle swarm optimization (PSO) algorithm is proposed as multipath routing algorithm. Link expiration time (LET) between each two nodes is used as the link reliability estimation metric. This approach can find either node-disjoint or link-disjoint paths in singlephase route discovery. Simulation results confirm that PSO-HNN routing algorithm has better performance as compared to backup path set selection algorithm (BPSA) in terms of the path set reliability and number of paths in the set.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Mansour Sheikhan
AU  - Ehsan Hemmati
PY  - 2012
DA  - 2012/06/01
TI  - PSO-Optimized Hopfield Neural Network-Based Multipath Routing for Mobile Ad-hoc Networks
JO  - International Journal of Computational Intelligence Systems
SP  - 568
EP  - 581
VL  - 5
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.696921
DO  - 10.1080/18756891.2012.696921
ID  - Sheikhan2012
ER  -