Energy‐Efficient User Association with Congestion Avoidance and Migration Constraint in Green WLANs

Abstract

Green wireless local area networks (WLANs) have captured the interests of academia and industry recently, because they save energy by scheduling an access point (AP) on/off according to traffic demands. However, it is very challenging to determine user association in a green WLAN while simultaneously considering several other factors, such as avoiding AP congestion and user migration constraints. Here, we study the energy-efficient user association with congestion avoidance and migration constraint (EACM). First, we formulate the EACM problem as an integer linear programming (ILP) model, to minimize APs' overall energy consumption within a time interval while satisfying the following constraints: traffic demand, AP utilization threshold, and maximum number of demand node (DN) migrations allowed. Then, we propose an efficient migration-constrained user reassociation algorithm, consisting of two steps. The first step removes AP-DN associations to eliminate AP congestion and turn off as many idle APs as possible. The second step reassociates these DNs according to an energy efficiency strategy. Finally, we perform simulation experiments that validate our algorithm's effectiveness and efficiency.

Optimal Access Point Power Management for Green IEEE 802.11 Networks

“…Wu et al [ 31 ] studied the user association problem in green WLANs, to minimise the network’s energy consumption while satisfying time-varying traffic demands. They formulated an integer linear programming able to take into account both AP congestion avoidance and user migration constraints.…”

Robust green Wireless Local Area Networks: A matheuristic approach

“…In Zhang et al (2018), a tabu-search algorithm is proposed to solve the problem of minimizing the power consumption by turning-off subsets of APs and assigning their users to other active APs without compromising the Quality-of-Service. In Wu et al (2018), a two-stage heuristic algorithm is proposed for the power consumption minimization: firstly, a limited number of AP-UT assignments is eliminated to reduce the traffic congestion and turn-off as many idle APs as possible; then, the unassigned UTs are reassigned to some APs by trying to improve the energy efficiency. In Gendron et al (2016) an efficient branch-andcut algorithm based on the principles of Benders' Decomposition is proposed to tackle large scale instances.…”