METHOD AND SYSTEM FOR OPTIMIZING WIRELESS NETWORKS THROUGH FEEDBACK AND ADAPTATION

• US 20090303888A1
• Filed: 09/19/2007
• Published: 12/10/2009
• Est. Priority Date: 05/03/2007
• Status: Abandoned Application

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: Yi, Yunjung, Ariyur, Kartik B., Varadarajan, Srivatsan
• Application Number:
  US11/857,748
• Publication Number:
  US 20090303888A1
• Time in Patent Office: Days
• US Class Current: 370/252
• CPC Class Codes: H04L 41/0816 the condition being an adaptation, e.g. in response to network events
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 43/0829 Packet loss
• CPC Class Codes: H04L 43/0852 Delays
• CPC Class Codes: H04L 43/0888 Throughput
• CPC Class Codes: H04L 43/091 Measuring contribution of individual network components to actual service level
• CPC Class Codes: H04W 16/20 for indoor coverage or short range network deployment
• CPC Class Codes: H04W 24/02 Arrangements for optimising operational condition
• CPC Class Codes: H04W 24/08 Testing, supervising or monitoring using real traffic
• CPC Class Codes: H04W 84/12 WLAN [Wireless Local Area Networks]
• CPC Class Codes: H04W 84/18 Self-organising networks, e.g. ad-hoc networks or sensor networks

Abstract

A method for optimizing a wireless network comprises obtaining local measurement and feedback data from a single node in the network; estimating a state of the node by using the local measurement and feedback data in an analysis framework model of the wireless network; applying the estimated state of the node to a local control law to determine one or more local protocol parameter updates for the node; and transmitting the one or more local protocol parameter updates to the node in the network. The method can further comprise obtaining global measurement and feedback data from one or more additional nodes in the network; estimating a state of the one or more additional nodes by using the global measurement and feedback data in the analysis framework model; applying the estimated state of the one or more additional nodes to the local control law; applying the estimated state of the one or more additional nodes to a global control law to determine one or more network-wide protocol parameter updates; and transmitting the network-wide protocol parameter updates to the network.

Claims

1. A method for optimizing a wireless network, the method comprising:

obtaining local measurement and feedback data from a single node in the wireless network;

estimating a state of the node by using the local measurement and feedback data in an analysis framework model of the wireless network;

applying the estimated state of the node to a local control law to determine one or more local protocol parameter updates for the node; and

transmitting the one or more local protocol parameter updates to the node in the wireless network.

2. The method of claim 1, further comprising:

obtaining global measurement and feedback data from one or more additional nodes in the wireless network;

estimating a state of the one or more additional nodes by using the global measurement and feedback data in the analysis framework model;

applying the estimated state of the one or more additional nodes to the local control law;

applying the estimated state of the one or more additional nodes to a global control law to determine one or more network-wide protocol parameter updates; and

transmitting the network-wide protocol parameter updates to the wireless network.

3. The method of claim 1, wherein the local measurement and feedback data comprises one or more of bit error rate, MAC losses, buffer losses, buffer drops, throughput on a path, throughput across a node, latency on a path, or latency across a node.

4. The method of claim 1, wherein the local measurement and feedback data lack communication overhead.

5. The method of claim 2, wherein the one or more additional nodes are not more than two hops from the single node.

6. The method of claim 1, wherein the analysis framework model computes the performance impact of a MAC layer and a network layer in the wireless network.

7. The method of claim 1, wherein the local protocol parameter updates provide for maximizing throughput while minimizing latency, or preserving throughput and latency.

8. The method of claim 2, wherein the network-wide protocol parameter updates provide for capacity maximization and loss minimization in the wireless network.

9. The method of claim 1, wherein the wireless network is an IEEE 802.11 network.

10. A computer readable medium having instructions stored thereon for a method of optimizing a wireless network according to claim 2.

11. A system for optimization of a wireless network, the system comprising:

a first state estimator module comprising an analytic framework model of the wireless network, the first state estimator module configured to receive local measurements from a node in the wireless network;

a second state estimator module comprising the analytic framework model, the second state estimator module configured to receive global measurements from the wireless network;

a local control law module configured to receive input data from the first and second state estimator modules, and configured to output local protocol parameter updates to the wireless network; and

a global control law module configured to receive input data from the second state estimator module, and configured to output network-wide protocol parameter updates to the wireless network.

12. The system of claim 11, wherein the analytic framework model combines network queuing and interference.

13. An adaptation framework system for network optimization, the system comprising:

an optimizer module comprising;

a tuner module including one or more search algorithms, the tuner module configured to tune one or more network parameters;

an analysis framework module in operative communication with the tuner module;

an output from the analysis framework module in operative communication with a wireless network; and

a feedback loop from the analysis framework module to the tuner module; and

an adaptation trigger operatively connecting the wireless network with the tuner module;

wherein a time slot size for packets in the wireless network is adaptively adjusted with the search algorithms to maximize network throughput and minimize network latency.

14. The system of claim 13, wherein the one or more search algorithms comprise a genetic algorithm, and a gradient-based search algorithm.

15. The system of claim 14, wherein the gradient-based search algorithm is an extremum seeking algorithm.

16. The system of claim 14, wherein the genetic algorithm is configured for use at system startup or periodically.

17. The system of claim 15, wherein the extremum seeking algorithm is configured for real-time adaptation to accommodate traffic load changes in the wireless network.

18. The system of claim 13, wherein the adaptation trigger is configured to be activated such that a new optimal parameter set is selected when needed.

19. The system of claim 13, wherein the wireless network comprises a sensor network, a mobile ad hoc network, or a wireless local area network.

20. The system of claim 13, wherein the wireless network comprises an IEEE 802.11 network.