A New Optimal Deployment Model Of Internet Of Things Based On Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are scalable research domain with a multitude of application contexts. Sensor nodes deployment is a decisive step that has a major impact on the performance of the network, since it directly influences the cost, the sensing capability and even the WSNs lifetimes. In this paper, we are interested in the placement problem of sensor nodes for WSNs. First, the issue is formulated as constrained multi-objective optimization problem (MOOP). Then, a novel approach based on Multi-Objective Flower Pollination Algorithm (MOFPA) was proposed. This new method aimed to approximate optimal trade-offs among multiple objective functions, which are enhancing the coverage, reducing the network energy dissipation, maximizing the network lifetime and maintaining the connectivity. Finally, we compared the proposed approach with two popular algorithms, namely, the classic Particle Swarm Optimization (PSO) and Non-dominated Sorting Genetic Algorithm II (NSGA-II). The simulation experiments show that our approach outperforms PSO and NSGA-II.