Energy-saving access point configurations in WLANs: a swarm intelligent approach

Wireless local area networks (WLANs) bring great convenience for people, however, they also consume a huge amount of energy, for most access points (APs) typically operate at the maximum transmit (TX) power all day. In this connection, this paper aims to minimize the overall TX power of all APs by jointly optimizing the location, state and TX power of each AP on the premise of full effective coverage. This paper considers not only three-dimensional scenarios with various obstacles, but also the fluctuation of user density in different time periods and different coverage intensity requirements. To solve the above problem, this paper proposes an improved elite golden jackal optimization (GJO) algorithm, named IEGJO, by introducing the global search strategy and elite evolution strategy into GJO. The performance of IEGJO was extensively evaluated and compared with eight state-of-the-art heuristic algorithms on 20 popular benchmark functions. The experimental results indicate that the IEGJO algorithm outperforms other algorithms in terms of comprehensive performance and ranks first. Then, this paper develops optimal AP configurations method based on IEGJO and applies it to optimize a WLAN in a campus building. The simulation results show that the total TX power of the system is reduced by 81.33%, while still guaranteeing the full effective coverage requirements. The source code is available on https://github.com/iNet-WZU/IEGJO.