Multi-vehicle Ad-hoc Network Routing Algorithm with Ant and Quantum Particle Swarm Optimization Combined

DOI

10.2991/iset-15.2015.11How to use a DOI?

Keywords

Vehicle self-organizing network, More routing algorithm, Ant colony, Quantum-behaved particle swarm

Abstract

In order to improve data transfer efficiency of the vehicle self-organizing networks and reduce end transmission delay, this paper presents a Multi-vehicle ad-hoc network routing algorithm with Ant and quantum particle swarm optimization combined (AQVT). The algorithm based on the thinking of ant colony algorithm that can find the optimal path, through distance relationship between vehicle and roadside access point and vehicle location information to as measures of ant search path, to find the optimal vehicles network routing. and uses the idea of QPSO algorithm that can global search to enhance the global convergence of the algorithm. Experimental results show that, compared MROFDM algorithm and DRIP algorithm, AQVT algorithm can achieve higher data delivery ratio and obtain a lower-end latency.

Copyright

© 2015, 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  - CONF
AU  - Zhiping Wan
PY  - 2015/03
DA  - 2015/03
TI  - Multi-vehicle Ad-hoc Network Routing Algorithm with Ant and Quantum Particle Swarm Optimization Combined
BT  - Proceedings of the First International Conference on Information Science and Electronic Technology
PB  - Atlantis Press
SP  - 41
EP  - 44
SN  - 2352-538X
UR  - https://doi.org/10.2991/iset-15.2015.11
DO  - 10.2991/iset-15.2015.11
ID  - Wan2015/03
ER  -