Fault-tolerance clustering algorithm with load-balance aware in wireless sensor network

作者：Su Jin Shu; Guo Wen Zhong^*; Yu Chao Long; Chen Guo Long

来源：Chinese Journal of Computers, 2014, 37(2): 445-456.

DOI：10.3724/SP.J.1016.2014.00445

• Adaptive discrete particle swarm optimization (ADPSO)
• Cluster-head selections
• Connectivity algorithms
• Internet of Things (IOT)
• Local Minimum Spanning tree
• Network energy consumption
• Network reliability
• Two-connectivity

Good clustering algorithm can effectively reduce network energy consumption and improve the reliability of network. However, load unbalance and communication unreliability between the clusters have significant impacts on the performance of the clustering algorithm. In this paper, a fault-tolerance clustering algorithm with load-balance aware was proposed to solve these problems. Base on the quality of the particles in the population, an adaptive discrete particle swarm optimization (ADPSO) with an adaptive adjustment strategy for inertia weight was designed, using the randomly two-point crossover operator and random one-point mutation operator of the genetic algorithm. We introduced a cluster head selection mechanism based on ADPSO for optimizing both of the two objects, load balancing and energy consumption in the algorithm. Moreover, to guarantee the reliability of data transmission, an inter-cluster connectivity algorithm based on local minimum spanning tree was constructed, which ensured the two-connectivity by eliminating cut point in the network. The experimental results demonstrate that the proposed algorithm can achieve better performance on load balancing and two-connectivity, effectively reducing the energy consumption, prolonging the lifetime of the network and improving the network reliability.

• 出版日期2014
• 单位福州大学