SLEEP MODE SELECTION EMPLOYING A SEMI-MARKOV DECISION PROCESS

• US 20120057513A1
• Filed: 12/01/2010
• Published: 03/08/2012
• Est. Priority Date: 09/08/2010
• Status: Active Grant

• Current Assignee: Hong Kong University of Science and Technology
• Original Assignee: Hong Kong University of Science and Technology
• Inventors: Wong, Ka Wai, Kong, Lei, Tsang, Danny Hin Kwok
• Granted Patent: US 8,565,134 B2
• Time in Patent Office: Days
• US Class Current: 370/311
• CPC Class Codes: H04W 52/0216 using a pre-established activity schedule, e.g. traffic indication frame
• CPC Class Codes: Y02D 30/70 in wireless communication networks

Abstract

The disclosed subject matter relates to energy efficiency in mobile devices associated with a wireless communications environment. Power Saving Classes (PSCs) aim to reduce the power consumption of mobile devices based on the different types of traffic. Optimizing sleep mode selection schemes so as to maximize the energy efficiency while providing a QoS guarantee can be accomplished with optimization of a theoretical framework based on the semi-Markov Decision Process along with a performance evaluation on the sleep mode operation. A novel Policy Optimization algorithm is capable of finding optimized policies for a selection of different PSCs.

Claims

1. A system that facilitates access to one or more sleep mode selection policies, comprising:

a semi-Markov decision process (MDP) component configured to access at least one wireless system parameter and determine the one or more sleep mode selection policies based on an MDP model.

2. The system of claim 1, wherein the at least one wireless system parameter includes a traffic demand parameter.

3. The system of claim 1, wherein the at least one wireless system parameter includes at least one of a mobile subscriber station parameter, a cost metric parameter, a quality of service parameter, or an optimization target.

4. The system of claim 1 further comprising a cost metric component configured to compute at least one cost metric value based on at least one corresponding action taken within the MDP model.

5. The system of claim 4, wherein the cost metric component is further configured to compute at least one cost metric value for at least one of a sleep ratio, an energy cost, or a packet delay.

6. The system of claim 1, further comprising a policy optimizer component configured to determine one or more optimized sleep mode selection policies as a subset of a total set of sleep mode policies.

7. The system of claim 6, wherein the one or more of the optimized sleep mode selection policies satisfy a quality of service requirement.

8. The system of claim 6, wherein the policy optimizer component is configured to apply a linear programming policy optimization algorithm during a determination of the one or more optimized sleep mode selection policies.

9. The system of claim 8, wherein the linear programming policy optimization algorithm minimizes a power consumption of the system subject to a delay constraint of the system.

10. The system of claim 1, wherein the one or more sleep mode selection policies are employed to determine at least one timeout delay value or a sleep mode transition value.

11. The system of claim 10, wherein the one or more sleep mode selection policies are in the form of one or more state-action frequencies translatable into one or more command probabilities.

12. The system of claim 1, wherein the wireless system employs wireless technologies conforming to the Institute of Electrical and Electronics Engineers (IEEE) 802.16e-2005 standard.

13. A method, comprising:

accessing at least one wireless system parameter;

determining at least one optimized sleep mode selection policy; and

facilitating access to the at least one optimized sleep mode selection policy.

14. The method of claim 13, wherein the wireless system employs wireless technologies conforming to the Institute of Electrical and Electronics Engineers (IEEE) 802.16e-2005 standard.

15. The method of claim 13, wherein the accessing includes accessing at least one of an expected sleep ratio, an expected power consumption level, or an expected packet delay value.

16. The method of claim 13, further comprising generating a timeout value or transition decision value based, at least in part, on the at least one optimized sleep mode selection policy.

17. The method of claim 16, wherein the at least one optimized sleep mode selection policy is in the form of a set of state-action frequencies translatable into a set of command probabilities.

18. The method of claim 13, wherein the optimized sleep mode selection policy further satisfies a quality of service requirement.

19. A method of optimizing sleep mode operation for a mobile subscriber station (MSS) in a wireless communications system, comprising:

modeling sleep mode operation of the MSS as a semi-Markov decision process (MDP) to facilitate computing performance evaluations of wireless power saving classes associated with the MSS and the wireless communications system;

modeling at least a cost function for at least a sleep mode behavior of the MSS; and

selecting at least an optimized sleep mode selection policy from a set of sleep mode selection policies for the MSS based at least in part on minimizing power consumption of the MSS.

20. An article of manufacture including a computer-readable medium having instructions stored thereon that, in response to execution by a computing device, cause the computing device to perform a method, comprising:

modeling a sleep mode of a mobile subscriber station (MSS) as a semi-Markov decision process (MDP) to facilitate evaluations of wireless power saving classes associated with the MSS and the wireless communications system;

modeling at least a cost function of the sleep mode; and

selecting at least an optimized sleep mode selection policy from a set of sleep mode selection policies for the MSS based at least in part on minimizing power consumption of the MSS.