| Popis: |
Wireless Sensor Networks (WSNs) are expected to serve vast number of applications including environmental monitoring applications. In such networks, sensor nodes have limited energy supply and processing power. Hence, random deployments may result in initial communication gaps and waste of energy resources. These gaps may still exist even after structured manner deployments. Similarly, in hierarchical wireless sensor networks, deploying large number of sensor nodes in addition to relays and clusterhead (CH) could improve connectivity but may result in increasing the overall cost with no guarantees for enhancing network lifetime. Therefore, in order to achieve better connectivity, extend network lifetime and minimize cost, a careful deployment of nodes is required. Such deployment is challenging due to the conflicting nature of the aforementioned objectives. It is even more challenging when nodes are deployed in 3-D dimensional space. This paper proposes a 3-D multi-objective deployment of WSNs based on a heuristic optimization approaches, namely Genetic Algorithm (GA) and Binary Particle Swarm Optimization (BPSO). The proposed WSN has a multi-dimensional (3-D) structure with a two-layer hierarchy consisting of sensor nodes, clusterheads and a base station. The aim is to obtain an optimal or near optimal positioning for clusterheads to satisfy the desired objectives. Experimental results show that the proposed method can enhance the network deployment when the three objectives are considered. |
