Cloud-based Management of Energy-Efficient Dense IEEE 802.11ax Networks

Abstract

During the last decade, the number of devices connected to the Internet by Wi-Fi has grown significantly. A high density of both the client devices and the hot spots posed new challenges related to providing the desired quality of service in the current and emerging scenarios. To cope with the negative effects caused by network densification, modern Wi-Fi is becoming more and more centralized. To improve network efficiency, today many new Wi-Fi deployments are under control of management systems that optimize network parameters in a centralized manner. In the paper, for such a cloud management system, we develop an algorithm which aims at maximizing energy efficiency and also keeps fairness among clients. For that, we design an objective function and solve an optimization problem using the branch and bound approach. To evaluate the efficiency of the developed solution, we implement it in the NS-3 simulator and compare with existing solutions and legacy behavior.

Joint optimization of target wake time mechanism and scheduling for IEEE 802.11ax

“…This mechanism is introduced to save more power by allowing users to have different sleeping periods. In [9,10], the authors are interested in reducing power consumption of 802.11ax based networks but by not directly attacking the TWT mechanism. Specifically, the work in [9] tries to save energy by developing a scheduling scheme for the case when OFDMA is used.…”

“…Specifically, the work in [9] tries to save energy by developing a scheduling scheme for the case when OFDMA is used. Also, a cloud-based centralized management is proposed for the energy saving of a dense network with many 802.11ax based APs in [10]. The "clock drift" problem which is the misalignment of the scheduling times of STAs within TWT mechanism and its effect on the power consumption is investigated in [11].…”