文献类型：期刊文献

英文题名：A Novel Energetic Ant Optimization Algorithm for Routing Network Analysis

作者：Feng, Xiang[1,2]; Xu, Hanyu[1]

机构：[1] Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, China; [2] Smart City Collaborative Innovation Center, Shanghai Jiao Tong University, Shanghai, China

年份：2018

卷号：10955 LNCS

起止页码：705

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20183505746876)

语种：英文

外文关键词：Artificial intelligence - Ad hoc networks - Ant colony optimization - Power management (telecommunication)

摘要：The latest biological research results show that it is natural to see that ants at different age group play roles and responsibilities differently. As inspired by the same, the concept of age and intra-groups is thus introduced into traditional Ant Colony Optimization (ACO) algorithm. A new intelligent parallel algorithm, Energetic Ant Optimization model (EAO), is put forward and applied for energy-aware routing network analysis. The proposed algorithm is designed to calculate the routing probability and phenomenon increment by taking the remaining energy of node as a heuristic factor. By EAO, the age of ant corresponds to the energy of the Ad Hoc network. Not only was mathematical model built for the EAO theoretically, but also its application was described detailedly. Finally, the proposed algorithm is simulated and analyzed in different scenarios, and the experimental results are compared with the results of Ad hoc on-demand distance vector routing (AODV). The simulation results show that EAO routing algorithm (EAORA) performs much better in packet delivery ratio, the average end-to-end delay and lifetime of network. Besides, the EAORA has better performance in balancing the energy consuming between nodes. ? Springer International Publishing AG, part of Springer Nature 2018.