Methodology for managing power consumption in master driven time division duplex wireless network

• US 6,807,159 B1
• Filed: 10/25/2000
• Issued: 10/19/2004
• Est. Priority Date: 10/25/2000
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Chakraborty, Indraneel, Rastogi, Anupam, Kashyap, Abhishek, Shorey, Rajeev, Kumar, Apurva, Saran, Huzur
• Primary Examiner(s): Lee, Andy
• Assistant Examiner(s): Juntima, Nittaya
• Application Number:
  US09/696,556
• Time in Patent Office: 1,455 Days
• Field of Search: 370/449, 370/318, 370/352, 370/322, 370/348, 370/346, 455/574, 455/343.1
• US Class Current: 370/318
• CPC Class Codes: H04L 12/12 Arrangements for remote connection or disconnection of substations or of equipment thereof
• CPC Class Codes: H04W 52/0212 managed by the network, e.g. network or access point is master and terminal is slave
• CPC Class Codes: H04W 52/0235 where the received signal is a power saving command
• CPC Class Codes: H04W 74/06 using polling
• CPC Class Codes: Y02D 30/70 in wireless communication networks

Abstract

A system, method, and computer program product for carrying out the method for managing power consumption in a master driven time division duplex wireless network comprising optimizing power consumption while maintaining quality of service requirements for end-to-end packet delay by adjusting the polling interval for each slave in low power mode based on the incoming traffic at the slave.

Claims

1. A system for managing power consumption in a master driven time division duplex wireless network comprising means for optimizing power consumption while maintaining quality of service requirements for end-to-end packet delay, by adjusting a polling interval for each slave in low power mode based on incoming traffic at the slave, wherein said means includes means for predicting an expected arrival time for the next packet at each slave based on a distribution of inter-arrival times for the previous packets received at that slave.

2. The system as claimed in claim 1, wherein said means for optimizing comprising Adaptive Probability based Polling interval (APPI) mechanism for adjusting the polling interval for each slave device in low power mode.

3. The system as claimed in claim 2, wherein said APPI mechanism comprises an APPI with fixed resolution or an APPI with adaptive resolution.

4. The system as claimed in claim 2, wherein said means for predicting the expected arrival time comprises:

means for learning a number of data bursts that arrive at each slave in particular ranges of inter-arrival times,

means for estimating a probability density function of the traffic distribution at each slave, and

means for determining the expected time interval for an arrival of the next data burst at each slave for which a probability of occurrence exceeds a defined threshold value.

5. The system as claimed in claim 4, wherein said means for learning the number of data bursts further comprises a means for receiving and storing the number of data bursts arriving in particular ranges of inter-arrival times in entries corresponding to said inter-arrival ranges.

6. The system as claimed in claim 4, wherein said means for estimating the probability density function further comprises a means for analyzing the distribution of data packets for different inter-arrival time durations.

7. The system as claimed in claim 4, wherein said means for determining the expected time interval for a defined threshold probability is described by:

8. The system as claimed in claim 2, wherein a slave is switched from active mode to low power mode based on a condition:

9. The system as claimed in claim 2, wherein said mechanism for adjusting the polling interval in low power mode is based on a tolerance of a connection of delayed packets and is defined by:

 

P(t)=₀Σ

^T_PH(x)≦

P_B

where

P(t) is a probability of arrival of a packet

T_P is a polling interval of the slave in low power mode

P_B is a probability, which reflects the tolerance of the connection for delayed packets

H(x) is a function defining a number of observed inter-arrival times for each inter-arrival period normalized by a total number of observations.

10. The system as claimed in claim 2, wherein a slave is switched from low power mode to active mode based on a condition:

11. The system as claimed in claim 1, wherein said master driven time division duplex wireless network is a Bluetooth network in which said low power mode corresponds to a “

SNIFF”

mode.

12. A method for managing power consumption in a master driven time division duplex wireless network, said method comprising optimizing power consumption while maintaining quality of service requirements for end-to-end packet delay, by adjusting a polling interval for each slave based on incoming traffic at the slave, wherein said method further includes predicting of an expected arrival time for the next packet at each slave based on a distribution of inter-arrival times for the previous packets at that slave.

13. The method as claimed in claim 12, wherein said adjusting of the polling interval is accomplished using an Adaptive Probability based Polling Interval (APPI) method for adjusting the polling interval for each slave device in low power mode.

14. The method as claimed in claim 13, APPI method comprises an APPI with fixed resolution or an APPI with adaptive resolution.

15. The method as claimed in claim 13, wherein predicting of the expected arrival time comprises:

learning a number of data bursts that arrive at each slave in particular ranges of inter-arrival times,

estimating a probability density function of the traffic distribution at each slave, and

determining the expected time interval for an arrival of the next data burst at each slave for which a probability of occurrence exceeds a defined threshold value.

16. The method as claimed in claim 15, wherein said learning of the number of data bursts is accomplished by storing the number of data bursts arriving in particular ranges of inter-arrival times in entries corresponding to said inter-arrival ranges.

17. The method as claimed in claim 15, wherein said estimating of the probability density function is by analyzing the distribution of data packets for different inter-arrival time durations.

18. The method as claimed in claim 15, wherein said determining of the expected time interval for a defined threshold probability is described by:

19. The method as claimed in claim 13, wherein a slave is switched from active mode to low power mode based on a condition:

20. The method as claimed in claim 13, wherein said method for adjusting the polling interval in low power mode is based on a tolerance of a connection of delayed packets and is defined by:

21. The method as claimed in claim 12, wherein a slave is switched from low power mode to active mode based on a condition:

22. The method as claimed in claim 12, wherein said master driven time division duplex wireless network is a Bluetooth network in which said low power mode corresponds to a “

SNIFF”

mode.

23. A computer program product comprising computer readable program code stored on computer readable storage medium embodied therein for managing power consumption in a master driven time division duplex wireless network comprising computer readable program code means for optimizing power consumption while maintaining quality of service requirements for end-to-end packet delay, by adjusting a polling interval for each slave based on incoming traffic at the slave, wherein said computer readable program code means includes computer readable program code means for predicting of an expected arrival time for the next packet at each slave based on a distribution of inter-arrival times for the previous packets at that slave.

24. The computer program product a claimed in claim 23, wherein said computer readable program code means for optimizing comprises an Adaptive Probability based Polling Interval (APPI) mechanism for adjusting the polling interval for each slave device in low power mode.

25. The computer program product as claimed in claim 24, APPI mechanism comprises an APPI with fixed resolution or an APPI with adaptive resolution.

26. The computer program product as claimed in claim 24, wherein said computer readable program code means for predicting the expected arrival time comprises:

computer readable program code means for learning a number of data bursts that arrive at each slave in particular ranges of inter-arrival times,

computer readable program code means for estimating a probability density function of the traffic distribution at each slave, and

computer readable program code means for determining the expected time interval for an arrival of the next data burst at each slave for which a probability of occurrence exceeds a defined threshold value.

27. The computer program product as claimed in claim 26, wherein said computer readable program code means for learning the number of data bursts stores the number of data burst arriving in particular ranges of inter-arrival times in entries corresponding to said inter-arrival ranges.

28. The computer program product as claimed in claim 26, wherein the computer readable program code means for estimating the probability density function analyzes the distribution of data packets for different inter-arrival time durations.

29. The computer program product as claimed in claim 24, wherein said computer readable program code means for estimating the expected time interval for a defined threshold probability is defined by:

30. The computer program product as claimed in claim 24, wherein a slave is switched from active mode to low power mode based on a condition:

31. The computer program product as claimed in claim 24, wherein the mechanism for adjusting the polling interval in low power mode is based on a tolerance of a connection of delayed packets and is defined by:

32. The computer program product as claimed in claim 24, wherein a slave is switched from low power mode to active mode based on a condition:

33. The computer program product as claimed in claim 23, wherein said master driven time division duplex wireless network is a Bluetooth network in which said low power mode corresponds to a “

SNIFF”

mode.