Sensor Placement Based on an Improved Genetic Algorithm for Connected Confident Information Coverage in an Area with Obstacles

This paper studies how to place the least number of sensor nodes to ensure confident information coverage in an area with obstacles, while maintaining the connectivity of the placed nodes. For this constrained optimization problem, we propose a sensor placement scheme based on an improved genetic algorithm with our new problem-specific operations, including the Delaunaytriangulation-based population initialization, the chromosome correction operation with new gene insertion and redundant gene removal to produce a valid chromosome ensuring both coverage and connectivity, the chromosome mirror-crossover operation to enable the production of better offsprings. Simulation results show that the proposed algorithm can find better placement schemes in terms of much fewer deployed nodes, compared with the peer algorithms.