Exact and approximate algorithms for clustering problem in wireless sensor networks

Clustering is an effective method for improving the network lifetime and the overall scalability of a wireless sensor network. The problem of balancing the load of the cluster heads is called load-balanced clustering problem (LBCP), which is an NP-hard problem. In this study, the authors use parameterised complexity to cope with this NP-hard problem. The authors show that LBCP can be solved by a k-additive approximation algorithm with a running time of 2 O ( k / log ⁡ k ) + O ( n ) , where k is an upper bound on the maximum load assigned to the cluster heads and n is the input size. Also, LBCP is FPT with respect to the maximum load of the sensor nodes and the number of sensor nodes. The authors propose an fpt-algorithm with respect to these parameters for this problem. In addition, they prove that LBCP is W [ 1 ] - hard when the number of the cluster heads is selected as the parameter.

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