PREDICTIVE DUTY CYCLE ADAPTATION SCHEME FOR EVENT-DRIVEN WIRELESS SENSOR NETWORKS

• US 20110317017A1
• Filed: 08/20/2010
• Published: 12/29/2011
• Est. Priority Date: 08/20/2009
• Status: Abandoned Application

• Current Assignee: Olympus Corporation, Purdue Research Foundation (The Trustees of Purdue University (d/b/a Purdue University))
• Original Assignee: Olympus Corporation, Purdue Research Foundation (The Trustees of Purdue University (d/b/a Purdue University))
• Inventors: Park, Johnny, Kak, Avinash, Iwaki, Hidekazu, Kosaka, Akio, Shin, Joonhwa
• Application Number:
  US13/254,555
• Publication Number:
  US 20110317017A1
• Time in Patent Office: Days
• US Class Current: 348/159
• CPC Class Codes: H04W 4/70 Services for machine-to-machine communication [M2M] or machine type communication [MTC]
• CPC Class Codes: H04W 72/12 Wireless traffic scheduling
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

Embodiments of a method for controlling access to a shared communications medium by a plurality of nodes are disclosed. The method may comprise predicting, for each node of the plurality of nodes, whether an event will occur within a sensing field of that node at a future time and adapting a communications schedule of each node in response to the prediction regarding that node. Wireless sensor networks and computer readable media implementing embodiments of a method for controlling access to a shared communications medium by a plurality of nodes are also disclosed.

Claims

1. A method for controlling access to a shared communications medium by a plurality of nodes, the method comprising:

predicting, for each node of the plurality of nodes, whether an event will occur within a sensing field of that node at a future time; and

adapting a communications schedule of each node in response to the prediction regarding that node.

2. The method of claim 1, wherein predicting whether an event will occur within a sensing field of each node at a future time comprises predicting whether a camera of each node will observe an object of interest at the future time.

3. The method of claim 1, wherein predicting whether an event will occur within a sensing field of each node at a future time comprises estimating a spatio-temporal event probability at each node of the plurality of nodes.

4. The method of claim 3, wherein estimating the STEP at each node of the plurality of nodes comprises integrating a position uncertainty of an event over the sensing field of each node at the future time.

5. The method of claim 3, wherein estimating the STEP at each node of the plurality of nodes comprises using a recursive parameter estimator.

6. The method of claim 5, wherein using a recursive parameter estimator comprises using one of a Kalman filter and a particle filter.

7. The method of claim 5, further comprising receiving or overhearing, with a first node of the plurality of nodes, a packet from a second node of the plurality of nodes, the packet including a measurement of an event.

8. The method of claim 7, further comprising estimating a new STEP at the first node by updating the recursive parameter estimator using the measurement of the event.

9. The method of claim 7, further comprising initializing a new instance of the recursive parameter estimator when the measurement is not within a predicted uncertainty region for the event.

10. The method of claim 7, further comprising terminating an instance of the recursive parameter estimator after a predefined period of time during which no packets including a new measurement of the event are received or overheard by the first node.

11. The method of claim 10, wherein the communications schedule of the first node is adapted to a lowest duty cycle in response to the termination of the instance of the recursive parameter estimator.

12. The method of claim 1, wherein adapting the communications schedule of each node comprises adjusting a duty cycle of a radio of each node.

13. The method of claim 12, wherein adjusting the duty cycle of the radio of each node comprises determining to which probability subspace of a predicted uncertainty region of an event each node belongs.

14. The method of claim 12, wherein adjusting the duty cycle of the radio of each node comprises exponentially varying a frame length utilized by each radio.

15. The method of claim 1, further comprising transmitting a packet containing a dedicated field, the dedicated field including a first bit indicating whether a node transmitting the packet is currently sensing an event.

16. The method of claim 15, wherein the dedicated field further includes a second bit indicating whether the node transmitting the packet is currently transferring event-related data.

17. One or more non-transitory, computer-readable media comprising a plurality of instructions which, when executed by a processor of a first node, cause the processor to:

predict whether an event will occur within a sensing field of the first node at a future time; and

adapt a communications schedule of the first node in response to the prediction, the communications schedule controlling access by the first node to a communications medium shared between a plurality of nodes.

18. The one or more non-transitory, computer-readable media of claim 17, wherein predicting whether an event will occur within a sensing field of the first node at a future time comprises predicting whether a camera of the first node will observe an object of interest at the future time.

19. The one or more non-transitory, computer-readable media of claim 17, wherein predicting whether an event will occur within a sensing field of the first node at a future time comprises estimating a spatio-temporal event probability at the first node.

20. The one or more non-transitory, computer-readable media of claim 19, wherein estimating the STEP at the first node comprises integrating a position uncertainty of an event over the sensing field of the first node.

21. The one or more non-transitory, computer-readable media of claim 19, wherein estimating the STEP at the first node comprises using a recursive parameter estimator.

22. The one or more non-transitory, computer-readable media of claim 21, wherein using a recursive parameter estimator comprises using one of a Kalman filter and a particle filter.

23. The one or more non-transitory, computer-readable media of claim 21, wherein the plurality of instructions further cause the processor to receive or overhear a packet from a second node of the plurality of nodes, the packet including a measurement of an event.

24. The one or more non-transitory, computer-readable media of claim 23, wherein the plurality of instructions further cause the processor to estimate a new STEP at the first node by updating the recursive parameter estimator using the measurement of the event.

25. The one or more non-transitory, computer-readable media of claim 23, wherein the plurality of instructions further cause the processor to initialize a new instance of the recursive parameter estimator when the measurement is not within a predicted uncertainty region for the event.

26. The one or more non-transitory, computer-readable media of claim 23, wherein the plurality of instructions further cause the processor to terminate an instance of the recursive parameter estimator after a predefined period of time during which no packets including a new measurement of the event are received or overheard by the first node.

27. The one or more non-transitory, computer-readable media of claim 26, wherein the communications schedule of the first node is adapted to a lowest duty cycle in response to the termination of the instance of the recursive parameter estimator.

28. The one or more non-transitory, computer-readable media of claim 17, wherein adapting the communications schedule of the first node comprises adjusting a duty cycle of a radio of the first node.

29. The one or more non-transitory, computer-readable media of claim 28, wherein adjusting the duty cycle of the radio of the first node comprises determining to which probability subspace of a predicted uncertainty region of an event the first node belongs.

30. The one or more non-transitory, computer-readable media of claim 28, wherein adjusting the duty cycle of the radio of the first node comprises exponentially varying a frame length utilized by the radio of the first node.

31. The one or more non-transitory, computer-readable media of claim 17, wherein the plurality of instructions further cause the processor to transmit a packet containing a dedicated field, the dedicated field including a first bit indicating whether the first node is currently sensing an event.

32. The one or more non-transitory, computer-readable media of claim 31, wherein the dedicated field further includes a second bit indicating whether the first node is currently transferring event-related data.

33. A wireless sensor network comprising:

a plurality of nodes, each node including a control circuit and a radio providing access to a communications medium shared between the plurality of nodes, the control circuit of each node being configured to (i) predict whether an event will occur within a sensing field of that node at a future time and (ii) adjust a duty cycle of the radio of that node in response to the prediction.

34. The wireless sensor network of claim 33, wherein each node comprises a camera and the control circuit of each node is configured to predict whether the camera of that node will observe an object of interest at the future time.

35. The wireless sensor network of claim 33, wherein the control circuit of each node is configured to predict whether an event will occur within a sensing field of that node at a future time by estimating a spatio-temporal event probability at that node.

36. The wireless sensor network of claim 35, wherein the control circuit of each node is configured to estimate a spatio-temporal event probability at that node by integrating a position uncertainty of an event over the sensing field of that node.

37. The wireless sensor network of claim 35, wherein the control circuit of each node is configured to estimate a spatio-temporal event probability at that node using a recursive parameter estimator.

38. The wireless sensor network of claim 37, wherein the recursive parameter estimator comprises one of a Kalman filter and a particle filter.

39. The wireless sensor network of claim 37, wherein the control circuit of each node is further configured to receive or overhear a packet from another node of the plurality of nodes via the radio, the packet including a measurement of an event.

40. The wireless sensor network of claim 39, wherein the control circuit of each node is further configured to estimate a new STEP at that node by updating the recursive parameter estimator using the measurement of the event.

41. The wireless sensor network of claim 39, wherein the control circuit of each node is further configured to initialize a new instance of the recursive parameter estimator when the measurement is not within a predicted uncertainty region for the event.

42. The wireless sensor network of claim 39, wherein the control circuit of each node is further configured to terminate an instance of the recursive parameter estimator after a predefined period of time during which no packets including a new measurement of the event are received or overheard by that node.

43. The wireless sensor network of claim 42, wherein the control circuit of each node is further configured to adjust the duty cycle of the radio of that node to a lowest duty cycle in response to the termination of the instance of the recursive parameter estimator.

44. The wireless sensor network of claim 33, wherein the control circuit of each node is configured to adjust a duty cycle of the radio of that node by determining to which probability subspace of a predicted uncertainty region of an event the that node belongs.

45. The wireless sensor network of claim 33, wherein the control circuit of each node is configured to adjust a duty cycle of the radio of that node by exponentially varying a frame length utilized by the radio of that node.

46. The wireless sensor network of claim 33, wherein the control circuit of each node is further configured to transmit a packet containing a dedicated field via the radio, the dedicated field including a first bit indicating whether that node is currently sensing an event.

47. The wireless sensor network of claim 46, wherein the dedicated field further includes a second bit indicating whether that node is currently transferring event-related data.