Joint deployment and sleep scheduling of the Internet of things

The Internet of things (IoT) provides an infrastructure to constructing smart cities. Through the installed IoT sensors in the city, a large amount of information of the city is detected and collected in a cloud center, which provides residents to have immediate and convenient services. To achieve the goal of smart cities, the fundamental challenge has been to minimize the energy consumption of the IoT sensor network, which is involved with the deployment and sleep scheduling of IoT sensors. Most of the previous related works proposed two-stage approaches to address deployment and sleep scheduling problems of IoT sensors separately. However, the deployment at the first stage influences the optimality of the sleep scheduling at the second stage significantly. Consequently, this work jointly considers deployment and sleep scheduling of IoT sensors in a smart city. To improve the performance of sleep scheduling of IoT sensors, the deployment at the first stage concurrently considers a part of the optimality of later sleep scheduling, and it is optimized by the proposed improved geometric selective harmony search algorithm that incorporates crossover and dynamic schemes. The crossover scheme can effectively solve the problem of different decision variables in the solution representation; and the dynamic scheme can increase stability and diversity of searching for solutions. The performance of the proposed algorithm is evaluated by the simulation under various combinations of covering requirements, the number of sensors, and practical parameter settings.