Affiliation:
1. School of Management, Henan University of Science and Technology, Luoyang 471003, P. R. China
2. Henan Collaborative Innovation Center of Nonferrous Metals, Luoyang 471003, P. R. China
Abstract
In view of the two shortcomings of the AODV routing protocol, they do not consider the bandwidth, delay and cost in the actual network, and the routing table has only one path from the basic node to the target node. This paper attempts to improve the AODV protocol by using particle swarm optimization. Through simulation experiments, this paper compares four improved particle swarm optimization algorithms, inertia weight, linear decline, shrinkage factor and chaos, and finds that ACPSO can find the optimal path faster and transmit data quickly. So, this paper uses chaotic particle swarm optimization (CACPSO) to improve AODV protocol. Finally, based on NS2 simulation platform, the improved AODV protocol is simulated and experimented. Different network environments are set up to test packet delivery rate, network delay and routing discovery frequency. The experimental results show that in the process of data transmission, the improved protocol has higher routing performance than AODV protocol, and can transmit data faster and more stably.
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Cited by
5 articles.
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