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  • 标题:Optimising social information by game theory and ant colony method to enhance routing protocol in opportunistic networks
  • 本地全文:下载
  • 作者:Chander Prabha ; Chander Prabha ; Ravinder Khanna
  • 期刊名称:Perspectives in Science
  • 印刷版ISSN:2213-0209
  • 电子版ISSN:2213-0209
  • 出版年度:2016
  • 卷号:8
  • 页码:658-660
  • DOI:10.1016/j.pisc.2016.06.050
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Summary The data loss and disconnection of nodes are frequent in the opportunistic networks. The social information plays an important role in reducing the data loss because it depends on the connectivity of nodes. The appropriate selection of next hop based on social information is critical for improving the performance of routing in opportunistic networks. The frequent disconnection problem is overcome by optimising the social information with Ant Colony Optimization method which depends on the topology of opportunistic network. The proposed protocol is examined thoroughly via analysis and simulation in order to assess their performance in comparison with other social based routing protocols in opportunistic network under various parameters settings.
  • 关键词:Opportunistic networks; Routing; Social information; Ant colony optimization; Disconnection;
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