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  • 标题:SAFM: An Adaptive Socially Aware Feedback Mechanism in Delay Tolerant Sensor Networks
  • 本地全文:下载
  • 作者:Yan Liu ; Kun Wang ; Guo Huang
  • 期刊名称:International Journal of Distributed Sensor Networks
  • 印刷版ISSN:1550-1329
  • 电子版ISSN:1550-1477
  • 出版年度:2015
  • 卷号:2015
  • DOI:10.1155/2015/971704
  • 出版社:Hindawi Publishing Corporation
  • 摘要:In Delay Tolerant Sensor Networks (DTSN), it is a challenge to ensure the delivery reliability, due to the lack of end-to-end path, intermittent connection, and high latency. In addition, the resource utilization is decreased because of the limited resources and a large number of redundant copies. To this end, this paper proposes an adaptive Socially Aware Feedback Mechanism (SAFM). In this mechanism, the historical information of the encountered nodes is utilized to construct social links which indicates the level of social relationship between nodes. In the feedback process, acknowledgements are forwarded to the nodes whose social link (SL) is higher than a given threshold α. After getting the acknowledgements, nodes will delete the copies of messages which have been received by the destination nodes, so as to reduce the redundancy. This mechanism is to reach a tradeoff between overhead and delivery efficiency. In simulation, the threshold α is obtained to reach the best performance of SAFM. Compared with active and passive receipt approaches in an acceptable range of delay, SAFM improves the delivery probability, decreases the buffer occupancy, and reduces the overhead.
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