Authors: Junyeop Lee SunKyum Kim JiHyeun Yoon SungBong Yang
Publish Date: 2015/01/29
Volume: 21, Issue: 6, Pages: 2055-2068
Abstract
We study a forwarding strategy in opportunistic networks which are one of the most challenging networks among mobile adhoc networks In opportunistic networks a node does not have knowledge about the entire network topology which is essential in the mobile adhoc network’s forwarding strategy Thus node behavior is exploited to calculate future contact opportunities for forwarding a message Utilizing social network analysis eg similarity and centrality has been proposed to improve the accuracy of the calculation task This paper proposes a forwarding strategy based on an analysis of network topology In the proposed strategy each node takes a sequence of snapshots of its firstorder neighbors during a warmup period Each node exchanges its own snapshots with each other and then aggregates the snapshots in order to extract the network topology information The extracted network topology is analyzed by social network analysis methods compactness and algebraic connectivity Forwarding decisions are made using the analysis of the features compactness and algebraic connectivity We present simulations using NS2 and the homecell communitybased mobility model to show that the proposed forwarding strategy results in delay performances similar to the epidemic forwarding scheme while maintaining reasonable network traffic In addition we demonstrate that the proposed strategy outperforms the SimBet and PRoPHET forwarding schemes with various communication ranges and memory space
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