Bio-inspired adaptive routing in self-organized networks: A survey

Xu Zhang, Yanling Zhang, Yang Li, Zhongshan Zhang*, Keping Long

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Since the study of collective behavior of social species can help humans manage complex systems, bio-inspired algorithms will consequently improve the routing performance in self-organized networks. A plethora of studies on adaptive routing in self-organized networks has already been carried out. In this paper, adaptive routing as one of important self-organization issues is surveyed. Several well-known bio-inspired adaptive routing algorithms, such as Ant Colony Optimization (ACO), AntNet, AntHocNet, BeeHive, Multiple Ant Colony Optimization (MACO), Multiple Ant-Bee Colony (MABC), as well as their merits and demerits are analyzed in detail. The remaining challenges to face in adaptive routing in the future are also discussed in this paper.

Original languageEnglish
Title of host publication2013 8th International ICST Conference on Communications and Networking in China, CHINACOM 2013 - Proceedings
Pages505-510
Number of pages6
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 8th International ICST Conference on Communications and Networking in China, CHINACOM 2013 - Guilin, China
Duration: 14 Aug 201316 Aug 2013

Publication series

Name2013 8th International ICST Conference on Communications and Networking in China, CHINACOM 2013 - Proceedings

Conference

Conference2013 8th International ICST Conference on Communications and Networking in China, CHINACOM 2013
Country/TerritoryChina
CityGuilin
Period14/08/1316/08/13

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