Gradient and Particle Swarm Optimization Based Hierarchical Cluster Algorithm in WSN
[1]Yan Xinfang,Yan Jingjing,Feng Yan.Gradient and Particle Swarm Optimization Based Hierarchical Cluster Algorithm in WSN[J].Journal of Zhengzhou University (Engineering Science),2016,37(02):33-36.[doi:10.3969/j.issn.1671-6833.201505017]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
37卷
Number of periods:
2016 02
Page number:
33-36
Column:
Public date:
2016-04-18
- Title:
- Gradient and Particle Swarm Optimization Based Hierarchical Cluster Algorithm in WSN
- Keywords:
- wireless sensor networks; gradient; particle swarm optimization; GPHCA; double cluster heads
- CLC:
- -
- DOI:
- 10.3969/j.issn.1671-6833.201505017
- Abstract:
- In order to balance the energy consumption of nodes in the network, a hierarchical clustering algorithm—GPHCA is proposed. This algorithm adopts the dual cluster head mode, and uses the particle swarm optimization algorithm to search for two nodes with large energy and small average distance to cluster members as the main cluster head. and the sub-cluster head to balance the burden of the cluster head on the two nodes; in the selection of the gateway, the energy and the total distance of the forwarding path are considered at the same time, so that the final selected gateway can be balanced in terms of energy and delay. The simulation results show that, The GPHCA algorithm can effectively prolong the life cycle of the network.
- References:
- -
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