Aiming at the problems of existing clustering routing algorithm of self-energized wireless sensor networks（WSNs） on fixed threshold for resurrection, incapacitates reappoint cluster head in the next round and lack o...Aiming at the problems of existing clustering routing algorithm of self-energized wireless sensor networks（WSNs） on fixed threshold for resurrection, incapacitates reappoint cluster head in the next round and lack of election limit, this paper proposes a novel clustering routing algorithm for self-energized WSNs clustering routing algorithm based on solar energy harvesting（CRBS） algorithm. The algorithm puts forward a threshold sensitive resurrection mechanism, reviving the node when harvesting energy reaches the set soft or hard energy threshold. Meanwhile, combined with current energy harvesting level, cluster head node can decide whether to reappoint the cluster head in the next round. What＇s more, CRBS optimizes the cluster head election threshold to limit the incompetent node in election. Combined with the solar energy harvesting simulation, the results show that CRBS algorithm can better keep the default cluster head proportion, and outperforms energy balanced clustering with self-energization（EBCS） algorithm in terms of surviving nodes number and the success ratio of data transmission展开更多
基金supported by the Natural Science Foundation Project of CQ CSTC (2012jj A40040)the Changjiang Scholars and Innovative Research Team in University (IRT1299)the Special Fund of Chongqing Key Laboratory (CSTC)
文摘Aiming at the problems of existing clustering routing algorithm of self-energized wireless sensor networks（WSNs） on fixed threshold for resurrection, incapacitates reappoint cluster head in the next round and lack of election limit, this paper proposes a novel clustering routing algorithm for self-energized WSNs clustering routing algorithm based on solar energy harvesting（CRBS） algorithm. The algorithm puts forward a threshold sensitive resurrection mechanism, reviving the node when harvesting energy reaches the set soft or hard energy threshold. Meanwhile, combined with current energy harvesting level, cluster head node can decide whether to reappoint the cluster head in the next round. What＇s more, CRBS optimizes the cluster head election threshold to limit the incompetent node in election. Combined with the solar energy harvesting simulation, the results show that CRBS algorithm can better keep the default cluster head proportion, and outperforms energy balanced clustering with self-energization（EBCS） algorithm in terms of surviving nodes number and the success ratio of data transmission
