Soft Computing

, Volume 21, Issue 24, pp 7313–7323 | Cite as

Novel PEECR-based clustering routing approach

Methodologies and Application


To solve the problem of unreasonable distribution of cluster heads in wireless sensor network (WSN) clustering routing methods, as well as to optimize data transferring between clusters, the novel predictive efficient energy consumption reclaim (PEECR)-based clustering routing approach for wireless sensor network has been presented in this paper. On how to select cluster head, a new energy-efficient clustering method based on degree, relative distance and residual energy of nodes is designed, which guarantees that distribution of cluster heads is uniform, scale of clusters is balanced, and nodes with high energy act as cluster head preferentially. By using swarm colony optimization idea, we design PEECR strategy for data transferring. A predictive data transferring strategy between clusters is designed. Taking expected energy consumption on a road, hops and propagation delay into account, definition of good ratio of a road is given, according to which we choose optimal road. In reception mode, energy consumption of transceivers from source node to sink node of wireless sensor network is similar to energy consumption from sink node to source node, and both can be minimized by our approach. Our experimental tests show that novel optimized clustering routing approach can improve quality of clusters and whole performance of network, reduce and balance energy consumption of the whole network, and prolong lifetime of WSN as well.


Clustering SCO PEECR Life cycle Data transferring 



This research work is supported by “863” project plan of China (No. 2007AA01Z188), National Natural Science Foundation of China (Nos. 61170173, 60773073 and 61001174), Program for New Century Excellent Talents in University of China (No. NCET-09-0895), Key project of Ministry of Education of China (No. 208010), Tianjin Natural Science Foundation (No. 10JCYBJC00500), Tianjin Key Natural Science Foundation (No. 13JCZDJC34600), Major projects of science and technology in Tianjin (No. 15ZXDSGX 00050), Training plan of Tianjin University Innovation Team (No. TD12-5016), Major Projects of Science and Technology for their services in Tianjin (No. 16ZXFWGX00010) and Training plan of Tianjin 131 Innovation Talent Team (No. TD2015-23).

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Tianjin Key Lab of Intelligent Computing and Novel Software TechnologyTianjin University of TechnologyTianjinChina
  2. 2.Key Laboratory of Computer Vision and System, Ministry of EducationTianjin University of TechnologyTianjinChina

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