ICCO: immune clustering-based coverage optimisation algorithm in wireless sensor networks

Characteristics of network itself and unpredictability of its working scenario may greatly affect the clustering topology and coverage performance, and further affect transmission reliability and robustness of the network. Topology control and coverage optimisation are the prior issues needed to be solved in wireless sensor network which can affect key performance of whole network. Biological immune algorithm is adopted as a novel effective method to the issues of clustering topology control and coverage optimisation in networks deployed by the static and movable nodes. Immune Clustering and Coverage Optimisation algorithm (ICCO) is proposed which includes Immune Clustering Optimisation algorithm (IClO) and Immune Coverage Optimisation algorithm (ICoO). First, Immune efficient clustering is completed in the scenario of static senor nodes and then hierarchical clustering topology control is established. Then, network coverage is optimised through dynamically and iteratively adjusting the positions of mobile sensor nodes by ICoO which is a multi-objective optimisation issue. Network coverage model and energy consumption model is established to analyse the network performance including algorithms' convergence, energy consumption and network area coverage. Simulations show that ICCO has realised the maximum coverage based on the robust immune topology with improved performance of fault tolerance by adjustment of movable nodes.