Wireless sensor network deployment optimisation based on coverage, connectivity and cost metrics

Wireless sensor network (WSN) deployment is still facing many challenges. These challenges are related to determining node positions that ensure a trade-off between different metrics such as coverage, k-coverage, connectivity and cost. Due to the high density of WSN, finding an optimal deployment becomes an NP-Hard task. In this paper, we study this problem of determining the optimal spatial node positions of WSN in indoor environments. We formulate this task as a constrained multi-objective optimisation problem (CMOOP). This formulation is based on mathematical modelling of the different above metrics. We explicit this original modelling and the CMOOP solving by genetic algorithm (GA) combined with the weighted-sum method. To prove the interest of the proposed methodology, the results of this work are presented and compared to other studies.