A Hierarchical Sub-Chromosome Genetic Algorithm (Hsc-ga) to Optimize Power Consumption and Data Communications Reliability in Wireless Sensor Networks

High reliability and low power consumption are among the major requirements in design of wireless sensor networks (WSNs). In this paper, a multi-objective problem is formulated as a Joint Power consumption and data Reliability (JPR) optimization problem. For this purpose, a connected dominating set (CDS)-based topology control approach is proposed. Our objective is to self-organize the network with minimum interference and power consumption. We consider the power changes into a topology with minimum CDS infrastructure subject to connectivity constraints. Since this problem is NP-hard, it cannot be dealt with using polynomial-time exact algorithms. Therefore, we first present a genetic algorithm taking into consideration problem-specific goals and constraints in an approximated manner called JPR Genetic Algorithm (Jpr-ga). Secondly, a Hierarchical Sub-Chromosome Genetic Algorithm (Hsc-ga) is proposed to obtain more accurate and faster solutions in the large and dense networks. We evaluate these algorithm over different networks topologies to analyse their efficiency. Comparing Jpr-ga and Hsc-ga with two different scenarios reveal that the proposed algorithms can efficiently balance power consumption and data communication reliability of sensor nodes and also prolong the network lifetime in WSNs.