Energy Efficient Schedulers in Wireless Networks: Design and Optimization

Minimizing energy consumption is crucial for portable wireless stations because they operate on a limited battery supply. For example, the IEEE 802.11 standard includes a mechanism called power-saving mode (PSM), which allows a network interface on a mobile station to enter a sleep state whenever possible to reduce its energy consumption. We consider a generic wireless system composed of an access point (AP) and several stations that offer a PSM to its users. Our PSM is AP-centric (i.e., gives control to the AP) to save more energy. We formulate a downlink scheduling optimization problem aimed at saving energy and propose two heuristic scheduling policies to solve it. One of these policies is non-work-conserving, and it offers an interesting tradeoff between energy consumption and user performance.We also study and show how the length of the Beacon Period (BP) has a significant impact on the energy and the delay performance of wireless stations. For each of our two scheduling policies, we derive simple approximate formulas for the length of the BP that minimizes the energy consumption and for the relationship between the delay performance and the length of the BP. Assuming the maximum allowable average packet delay is given by the users as a QoS requirement, we illustrate how to dimension the length of the BP for the two schedulers we have proposed and show that we can achieve significant energy savings while meeting the delay constraint with the non-work conserving one in many cases. Extensive simulations show that a fine-tuning of the length of the BP as well as well-designed scheduling disciplines is essential to saving energy in wireless stations.

[1]  Jean C. Walrand,et al.  High-performance communication networks , 1999 .

[2]  Randy H. Katz,et al.  Measuring and Reducing Energy Consumption of Network Interfaces in Hand-Held Devices (Special Issue on Mobile Computing) , 1997 .

[3]  Adam Wolisz,et al.  A trace-based approach for determining the energy consumption of a WLAN network interface , 2002 .

[4]  Gustavo de Veciana,et al.  Energy efficiency of centrally controlled transmission of fixed size packets , 2000, 2000 IEEE Wireless Communications and Networking Conference. Conference Record (Cat. No.00TH8540).

[5]  Martin Nilsson,et al.  Investigating the energy consumption of a wireless network interface in an ad hoc networking environment , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[6]  Wayne E. Smith.  Various optimizers for single‐stage production , 1956 .

[7]  J. Flinn,et al.  Energy-aware adaptation for mobile applications , 1999, SOSP.

[8]  Hari Balakrishnan,et al.  Minimizing Energy for Wireless Web Access with Bounded Slowdown , 2002, MobiCom '02.

[9]  Catherine Rosenberg,et al.  Energy Efficient Scheduler Design in Wireless Networks , 2004 .

[10]  Adam Wolisz,et al.  Power-saving mechanisms in emerging standards for wireless LANs: the MAC level perspective , 1998, IEEE Wirel. Commun..

[11]  Ronald W. Wolff,et al.  Stochastic Modeling and the Theory of Queues , 1989 .

[12]  Pravin Varaiya,et al.  High-performance communication networks (2nd ed.) , 1999 .

[13]  A. M. Abdullah,et al.  Wireless lan medium access control (mac) and physical layer (phy) specifications , 1997 .

[14]  Jean Walrand,et al.  CHAPTER 11 – Optical Networks , 2000 .

[15]  Robin Kravets,et al.  Power management techniques for mobile communication , 1998, MobiCom '98.