Novel Technique for Client-Side Passive Detection of WiFi Access Point Load
Tech ID: 16-066
Inventors: Dr. Aaron Striegel, Dr. Lixing Song
Date Added: August 12, 2019
A method to passively monitor the loading on a Wi-Fi network access point for more effective and efficient network characterization.
Currently, the displays of available Wi-Fi networks on a mobile device indicate only the potential peak performance, rather than the actual usable capacity. Therefore, despite strong signal strength, response times may be painfully slow due to a channel being heavily loaded with users.
Researchers at the University of Notre Dame have developed a method to passively monitor the loading on an access point providing a more effective and efficient network characterization. Unlike existing network characterization mobile applications, the passive method constantly scans for channel loading and potential interference thus eliminating the need to manually initialize tests. Additionally, this passive technology displays results more quickly, requires less bandwidth, and uses less energy than active applications. This method interprets the load on each channel through intelligent inferencing of the aggregation levels and rate levels. The channel loading measurement capabilities of this technology will enable Internet of Things (IoT) devices in any in-home network systems to communicate with one another in order to properly allocate channel loading and thus improve the network experience for all devices.
- Operates during normal Wi-Fi scanning procedures and measures 802.11 Wi-Fi networks (the global standard), minimizing implementation costs
- Passive detection does not require manual initiation, displays results instantly (opposed to approximately 10 seconds for active detection technologies), and requires less bandwidth than active detection
- Potential to be integrated with Internet of Things devices
Technology Readiness Status
TRL 4 - Prototype Validation
A prototype has been built and tested successfully in an environment with more than 75 devices connected to the network.