DYNAMICALLY ADJUSTING NETWORK PARAMETERS USING WEATHER FORECASTS

• US 20140372577A1
• Filed: 06/18/2013
• Published: 12/18/2014
• Est. Priority Date: 06/18/2013
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Hui, Jonathan W., Hong, Wei, Vasseur, Jean-Philippe
• Granted Patent: US 9,692,644 B2
• Time in Patent Office: Days
• US Class Current: 709/221
• CPC Class Codes: H04L 41/0816 the condition being an adaptation, e.g. in response to network events
• CPC Class Codes: H04L 41/0836 to enhance reliability, e.g. reduce downtime
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04W 40/18 based on predicted events
• CPC Class Codes: Y02D 30/70 in wireless communication networks
• CPC Class Codes: Y04S 40/00 Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
• CPC Class Codes: Y04S 40/18 Network protocols supporting networked applications, e.g. including control of end-device applications over a network

Abstract

In one embodiment, network parameters are dynamically adjusted using weather forecasts. The embodiments include determining a weather forecast that predicts a weather condition proximate to a network. Network parameters are then selected for adjustment based on the predicted weather condition. The selected network parameters are adjusted to improve performance of the network in response to the predicted weather condition.

Claims

1. A method, comprising:

determining a weather forecast that predicts a weather condition proximate to a network;

selecting network parameters of the network to adjust based on the predicted weather condition; and

adjusting the network parameters to improve performance of the network in response to the predicted weather condition.

2. The method according to claim 1, further comprising:

determining a plurality of network profiles that define attributes of the network and correspond to a plurality of weather conditions respectively; and

selecting a network profile that corresponds to the predicted weather condition, wherein

the selecting of network parameters is based on the selected network profile.

3. The method according to claim 1, wherein the adjusted network parameters include parameters from a plurality of layers in a network stack of the network.

4. The method according to claim 1, wherein the network parameters are adjusted before the predicted weather condition occurs.

5. The method according to claim 1, further comprising:

predicting future energy resources of an energy harvesting device connected to the network based on the predicted weather condition, wherein

the adjusting of the network parameters is based on the predicted future energy resources.

6. The method according to claim 1, further comprising:

receiving a message that indicates attributes of a network device that is subject to be affected by the predicted weather condition, wherein

the adjusting of the network parameters is based on the attributes of the network device.

7. The method according to claim 1, further comprising:

selecting nodes of the network based on the predicted weather condition, wherein

the adjusting of the network parameters only affects the selected nodes of the network.

8. The method according to claim 1, further comprising:

determining a time period during which the network parameters are to be adjusted, wherein

the network parameters are adjusted during the determined time period.

9. The method according to claim 2, further comprising:

obtaining feedback on network performance during or after a time at which the predicted weather condition occurs; and

adjusting a network profile based on the obtained feedback.

10. The method according to claim 1, wherein the network parameters are selected by a network management system (NMS) or a Field Area Router (FAR).

11. The method according to claim 2, wherein the attributes of the network defined by the plurality of network profiles include application traffic profiles and application usage requirements.

12. The method according to claim 1, wherein the network is a low power and lossy network (LLN).

13. An apparatus, comprising:

at least one network interface that communicates with a network;

a processor coupled to the at least one network interface and configured to execute a process; and

a memory configured to store program instructions which contain the process executable by the processor, the process comprising;

determining a weather forecast that predicts a weather condition proximate to the network;

selecting network parameters of the network to adjust based on the predicted weather condition; and

adjusting the network parameters to improve performance of the network in response to the predicted weather condition.

14. The apparatus according to claim 13, wherein the process further comprises:

generating a plurality of network profiles that define attributes of the network and correspond to a plurality of weather conditions respectively; and

selecting a network profile that corresponds to the predicted weather condition, wherein

the selecting of network parameters is based on the selected network profile.

15. The apparatus according to claim 13, wherein the adjusted network parameters include parameters from a plurality of layers in a network stack of the network.

16. The apparatus according to claim 13, wherein the network parameters are adjusted before the predicted weather condition occurs.

17. The apparatus according to claim 13, wherein the process further comprises:

predicting future energy resources of an energy harvesting device connected to the network based on the predicted weather condition, wherein

the adjusting of the network parameters is based on the predicted future energy resources.

18. The apparatus according to claim 13, wherein the process further comprises:

receiving a message that indicates attributes of a network device that is subject to be affected by the predicted weather condition, wherein

the adjusting of the network parameters is based on the attributes of the network device.

19. The apparatus according to claim 13, wherein the process further comprises:

selecting nodes of the network based on the predicted weather condition, wherein

the adjusting of the network parameters only affects the selected nodes of the network.

20. The apparatus according to claim 13, wherein the process further comprises:

determining a time period during which the network parameters are to be adjusted, wherein

the network parameters are adjusted during the determined time period.

21. The apparatus according to claim 14, wherein the process further comprises:

obtaining feedback on network performance during or after a time at which the predicted weather condition occurs; and

adjusting a network profile based on the obtained feedback.

22. The apparatus according to claim 13, wherein the network parameters are selected by a network management system (NMS) or a Field Area Router (FAR).

23. The apparatus according to claim 14, wherein the attributes of the network defined by the plurality of network profiles include application traffic profiles and application usage requirements.

24. The apparatus according to claim 13, wherein the network is a low power and lossy network (LLN).

25. A tangible non-transitory computer readable medium storing program instructions that cause a computer to execute a process, the process comprising:

determining a weather forecast that predicts a weather condition proximate to a network;

selecting network parameters of the network to adjust based on the predicted weather condition; and

adjusting the network parameters to improve performance of the network in response to the predicted weather condition.