局部最优聚类对RFID阅读器防碰撞的影响:对阅读器的公平性

Joongheon Kim, Wonjun Lee, Jieun Yu, Jihoon Myung, Eunkyo Kim, Choonhwa Lee
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引用次数: 50

摘要

本文提出了一种独特的RFID网络分层聚类的自适应动态定位方案,同时减少了聚类的重叠区域,从而减少了RFID阅读器之间的碰撞。利用我们的LLC方案来调整簇覆盖范围以最小化能耗,本文提出了RFID网络的低能量局部聚类(LLCR)解决RFID读写器防碰撞问题。LLCR是一种RFID读取器防碰撞算法,通过最小化每个RFID读取器覆盖的簇的重叠区域来最小化碰撞。LLCR考虑了每个RFID阅读器的能量状态以及RFID阅读器的碰撞。对于能量状态因子,我们根据每个RFID阅读器的计算能力来区分同质RFID网络和异构RFID网络。因此,我们针对每种情况设计了高效的同llcr和异llcr方案。我们基于仿真的性能评估表明,LLCR最大限度地减少了RFID读取器集群的能耗和重叠区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effect of localized optimal clustering for reader anti-collision in RFID networks: fairness aspects to the readers
This paper proposes an adaptive and dynamic localized scheme unique to hierarchical clustering in RFID networks, while reducing the overlapping areas of clusters and consequently reducing collisions among RFID readers. Drew on our LLC scheme that adjusts cluster coverage to minimize energy consumption, low-energy localized clustering for RFID networks (LLCR) addresses RFID reader anti-collision problem in this paper. LLCR is a RFID reader anti-collision algorithm that minimizes collisions by minimizing overlapping areas of clusters that each RFID reader covers. LLCR takes into account each RFID reader's energy state as well as RFID reader collisions. For the energy state factor, we distinguish homogeneous RFID networks from heterogeneous ones according to computing power of each RFID reader. Therefore, we have designed efficient homo-LLCR and hetero-LLCR schemes for each case. Our simulation-based performance evaluation shows that LLCR minimizes energy consumption and overlapping areas of clusters of RFID readers.
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