Lagrangian-Relaxation-Based Self-Repairing Mechanism for Wi-Fi Networks

Abstract

Wi-Fi was developed to support software-defined networks that are crucial for achieving high quality of service for next generation wireless networks. In this software-defined networking technology, network resources are utilized to reduce the effects of several influential factors such as the limited number of nonoverlapping channels, co-channel interference, rapidly changing distribution of customers, and access point (AP) failure. These factors cause irregular network traffic and service unavailability in some users. In this paper, we address the problems causing the AP failure and interference. The studied problems were modeled as linear and nonlinear mathematical programming problems. The Lagrangian relaxation approach, which is a type of divide-and-conquer method, was used to solve the load distribution problems near optimally. A self-repairing heuristic multiple-level load-balancing traffic adjustment was proposed to manage the problems pertaining to the AP failure. The delay difference metric, which is defined as the difference between tolerable delay and transmission delay, was used to evaluate the difference between the upper bound and lower bound of the delay. Moreover, the metric was used to estimate the improvement ratio between the existing methods and the proposed method. Modifiable transmission power ranges (which involve the cell breathing method) and association managements are adjusted to minimize the narrow gap and improve the self-repairing performance. Thus, resources are appropriately allocated to users, and adequate QoS is attained.