Research On Dynamic Resource Provisioning For Energy Efficiency In Dense Wireless Local Area Networks

Currently, increasing number of access points(AP s) are being deployed in enterprise offices, campuses and municipal downtowns for flexible Internet connectivity and to facilitate management. The primary purpose of these deployments is to satisfy user demand for high bandwidth, mobility, and reliability. However, some study of such WLANs showed that these networks are rarely used at the peak capacity, and the majority of the resources are idle or redundant most of the time, which causes significant energy waste. Therefore, with respect to the issue of power conservation, applying energy efficient strategies in WIFI network is strongly advocated. One feasible method is dynamically managing network resources. In this paper, we bring to attention that a large fraction of idle WLAN resources results in significa nt energy losses, propose several techniques for energy efficiency in WLANs,and combining necessary control schemes we propose a new algorithm based on dynamic resource provisioning for energy efficiency in dense WLANs.Firstly, in this paper, a new green clustering algorithm based on propagation analysis and optimization procedure is proposed to be as a first approach in the framework of an energy efficient strategy for dense WLANs. Traditionally, to maintain the network coverage, all the APs within the WLAN have to be powered-on. Nevertheless, the new algorithm can power-off a large proportion of APs, while the coverage is maintained as its always-on counterpart. The two main components of the new approach are the faster procedure based on K-means and the more accurate procedure based on Evolutionary Algorithm(EA), respectively. The two procedures are processes in parallel for different designed requirements. To implement the new algorithm, EA is applied to handle the optimization of multiple objectives. This paper also presents simulation s in scenarios modeled with ray-tracing method and FDTD technique, and the results show that approximately 67% to 90% of energy consumption can be saved, while it is able to maintain the original network coverage during periods when few users are online or the traffic load is low.Secondly, a novel access point deployment approach for energy efficiency in WIFI network is proposed. For better performance of power conservation, energy efficiency should be made as a designed goal and a built-in feature. The problem of AP deployment is described as a multi-objective optimization, the goal of which is to maintain the basic network coverage with relatively less APs. To estimate the coverage, an indoor propagation and penetration model based on the combination of ray-tracing algorithm, FDTD(finite-difference time-domain) technique, and rough set theory is presented; and, Dynamic Population Size Multiple Objective Particle Swarm Optimization(DPS-MOPSO) is introduced to handle the optimization problem. This paper also presents simulations in two scenarios, and the results show that the proposed method can be the guidance for AP deployment. Comparing with the results of green clustering, AP deployment future enhances the energy efficiency of dense WLANs approximately 10%.Thirdly, a temporary access selection based on the throughput analysis and battery life is proposed to improve the performance of networks and the experience of end users. Energy efficiency is achieved by dynamically managing network resources. Once the number of users that are online or th e traffic load increases, several APs are powered-on according to the policy. However, when an AP is powered on, the device is initialized through a long boot time, during which period clients cannot be associated with it. In this paper, based on throughput and battery life the issue of access selection is handled. Moreover, this paper demonstrates the feasibility and performance of Temporary Access Selection through experiments and simulations with Network Simulator version 3(NS-3), and the results show that while maintaining the required time efficiency by the temporary access, applying the new algorithm can improve the throughput and frustrate the packet loss by providing the proper candidate AP.Lastly, with the proposed methods and the mechanism of m anagement, we proposed a new algorithm based on dynamic resource provisioning for energy efficiency in dense WLANs. By comparing with the existed algorithms, the results show that while maintaining the network coverage and Qo S, our strategy achieves the minimum power consumption of the experimental network. To be specific, approximately 80% of energy consumption can be saved comparing with the situations that energy efficient strategies are not applied; and, comparing with the existed algorithms, the proposed method future enhances the energy efficiency of dense WLANs approximately 20% to 30%.