Research Article
A Comprehensive Cellular Learning Automata Based Routing Algorithm in Opportunistic Networks
@INPROCEEDINGS{10.1007/978-3-030-62205-3_4, author={Feng Zhang}, title={A Comprehensive Cellular Learning Automata Based Routing Algorithm in Opportunistic Networks}, proceedings={Mobile Wireless Middleware, Operating Systems and Applications. 9th EAI International Conference, MOBILWARE 2020, Hohhot, China, July 11, 2020, Proceedings}, proceedings_a={MOBILWARE}, year={2020}, month={11}, keywords={Opportunistic networks Routing algorithm Energy efficient Cellular learning automata Ambient intelligence}, doi={10.1007/978-3-030-62205-3_4} }- Feng Zhang
Year: 2020
A Comprehensive Cellular Learning Automata Based Routing Algorithm in Opportunistic Networks
MOBILWARE
Springer
DOI: 10.1007/978-3-030-62205-3_4
Abstract
A distinctive cellular learning automata based routing algorithm is proposed which exploits the ambient nodes feature to polish up the performance of opportunistic networks. The factors of each phase in the routing procedure of store-carry-forward are taken into account. Messages would be dropped on the basis of the dropping probability when congestion occurs during the store phase. Energy consumption would be balanced according to the threshold set by the node itself which is used to accept messages in the carry phase. Connection duration between nodes has been estimated to reduce the energy waste caused by fragment messages transmission during the forwarding process. To evaluate the validity of our proposed algorithm, we conduct comprehensive simulation experiments on the ONE platform. The results show that the proposed routing algorithm achieves higher delivery ratio and less overhead ratio. In addition, it gains a balance of energy consumption and an enhancement of the whole network performances.
