Wireless Sensor Networks Management Using Differential Evolution and Minimum Dominating Sets

Challenges of managing and controlling wireless sensor networks (WSNs) includes efficient routing, increasing sensor node lifetime by conserving energy consumption, and base stations fault-tolerance. These challenges can be solved by help of Minimum Dominating Set (MDS) algorithms. By applying MDS to WSNs, only base stations (dominating sensors) take the burden of the communication instead of all sensors, and consequently saving the communication bandwidth, energy consumption, and increase the network lifetime. In addition to that, having multiple MDS improve base stations fault tolerance by scheduling different MDS periodically. In this research, a new Differential Evolutionary (DE) is composed to solve the general MDS problem. First, this problem is formulated as a binary optimization problem. Then, new evolutionary operations are introduced to fit the considered problem and wireless sensor network applications. Beside these evolutionary operations, other search enhancement operations are invoked to improve the search diversification and intensification process in addition to enabling the search process to find several distinct solutions. Those solutions can help in scheduling the network control nodes in order to increase its lifetime. Several experimental simulations over benchmark networks are carried out to test the efficiency of the proposed method. The results demonstrate the quality of the proposed method for obtaining minimum dominating sets for the considered test networks.