Abstract
Opportunistic social network enables users to form an instant network for information sharing, which is a type of multi-hop wireless network in nature, thus relies on cooperation between nodes to complete message transmission. At present, most traditional routing algorithms require relay nodes to unconditionally forward received data. However, due to the limited of network resources, not all nodes are willing to forward data for other nodes, which is manifested as refusing to accept or even discarding messages, leading to deterioration of network performance. In this regard, this paper proposes an effective positive transmission routing algorithm (EPTR) based on social relationships in opportunistic social networks. This technology optimizes the method of community division by modularity, which not only considers the tightness of networks, but also discusses the social attributes of nodes. In this scheme, nodes with high relationship strength are selected to participate in data forwarding process, which makes packets are transmitted in the direction of increasing forwarding capability of nodes to the destination community. Simulation results show that the proposed algorithm can discover most abnormal nodes including malicious nodes and selfish nodes. Besides, compared with EIMCT algorithm, ITPCM algorithm and Spray and Wait algorithm, the proposed scheme has the highest transmission success rate and the lowest network load.
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Conceptualization, P.Z. and Y.Y.; Methodology, P.Z.; Software, Y.Y.; Validation, P.Z.; Formal Analysis, P.Z. and Y.Y.; Investigation, P.Z. and Y.Y.; Resources, P.Z.; Data Curation, P.Z. and Y.Y.; Writing—Original Draft Preparation, P.Z.; Writing—Review & Editing, P.Z.; Visualization, Y.Y.; Supervision, H.F.; Project Administration, H.F.; Funding Acquisition, H.F.
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Peng Zheng, Hongxiao Fei and Yeqing Yan contributed equally to this work.
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Zheng, P., Fei, H. & Yan, Y. An effective positive transmission routing algorithm based on social relationships in opportunistic social networks. Peer-to-Peer Netw. Appl. 13, 269–286 (2020). https://doi.org/10.1007/s12083-019-00767-7
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DOI: https://doi.org/10.1007/s12083-019-00767-7