Energy-Efficient WLANs With Resource and Re-Association Scheduling Optimization

Recently, a number of WiFi access points (APs) have been densely deployed to provide widely available, high-performance Internet services. As such, an energy efficiency issue becomes crucial toward the design of green wireless local area networks (WLANs). In this paper, we propose a resource and re-association scheduling algorithm (referred to RAS) based on Benders' decomposition to reduce the energy consumption. In particular, we endeavor to aggregate WLAN users on the small number of APs and turn off many APs without compromising users' quality of experience (QoE) and system coverage. We conduct the analysis by using real trace data and formulate the energy minimization as the mixed integer nonlinear programming (MINLP) problem. We then transform and solve the original problem through the RAS algorithm. For practical implementation, we further propose the fast RAS (Fast-RAS) algorithm to relax the binary integer constraints and transform the MINLP problem into the nonlinear programming (NLP) problem. The relaxed problem then can be solved by using Feasible Pump algorithm with the reduced computational complexity. We evaluate the performance of RAS and Fast-RAS algorithms via extensive simulations. The results demonstrate that the Fast-RAS algorithm can achieve up to 20% improvement of energy saving comparing with existed methods.