2015
DOI: 10.1186/s13638-015-0399-x
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A new clustering routing method based on PECE for WSN

Abstract: A new clustering routing method based on predictive energy consumption efficiency (PECE) for a wireless sensor network (WSN) is presented in this paper. It consists of two stages: cluster formation and stable data transfer. In the cluster formation stage, we design an energy-saving clustering routing algorithm based on the node degree, the relative distance between nodes, and the rest energy of nodes. When this algorithm selects the cluster head, the node degree and the relative distance between the nodes are … Show more

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Cited by 71 publications
(38 citation statements)
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“…[13][14][15][16][17][18][19] The fusion technique also presents an interesting strategy to solve this problem. [13][14][15][16][17][18][19] The fusion technique also presents an interesting strategy to solve this problem.…”
Section: Figurementioning
confidence: 99%
See 1 more Smart Citation
“…[13][14][15][16][17][18][19] The fusion technique also presents an interesting strategy to solve this problem. [13][14][15][16][17][18][19] The fusion technique also presents an interesting strategy to solve this problem.…”
Section: Figurementioning
confidence: 99%
“…Energy consumption remains the most critical challenge, which leads to developing many new strategies such as routing protocols. [13][14][15][16][17][18][19] The fusion technique also presents an interesting strategy to solve this problem. 20,21 Several other methods have been established to reach the same goal, such as the anti-collision algorithm, 22 which consists of mapping correlation of identification (ID) for radio frequency identification (RFID).…”
Section: Figurementioning
confidence: 99%
“…New clustering routing method i.e. predictive energy consumption efficiency (PECE) has been proposed for WSNs (Zhang et al, 2015). This protocol works in two stages: cluster formation and stable data transfer.…”
Section: Network Protocol and Topologymentioning
confidence: 99%
“…This method has accurate and stable merit. T. Ojala proposed a moving target with big data detection method based on optical flow and level set [24][25][26]. It can use target edge closed curve which can be obtain by the energy function to complete detection.…”
Section: Related Workmentioning
confidence: 99%