Compound Event Barrier Coverage Algorithm Based on Environment Pareto Dominated Selection Strategy in Multi-Constraints Sensor Networks

There are a variety of complex constraints in the wide application of wireless sensor networks. Traditional coverage models and algorithms have been unable to meet the needs of multi-constrained sensor networks. At the same time, in a complex monitoring environment, a single type of sensor information cannot meet the requirements of reliable monitoring. Hence, in this paper, aiming at the multi-constraints in sensor networks, a compound event barrier coverage algorithm is proposed based on environment Pareto-dominated selection strategy, which can distribute the sensor resources reasonably and find out the coverage ratio efficiently in multi-constraints sensor networks. The proposed algorithm takes advantage of Pareto domination relationship, constraint violation degree, constraint boundary distance, and crowding degree to preserve the outstanding infeasible individuals in the evolutionary process and participate in the mutation operation; we also adopt the adaptive scaling factor and crossover probability strategy to avoid the algorithm into local optimal. The proposed algorithm is proved to be more highly efficient than the latest algorithm in the distribution of sensor resources by experimental results.