Abstract
Techniques are presented herein that support a novel method through which received signal strength indication (RSSI) values and data from either a standards-based protocol (such as the Link Layer Discovery Protocol (LLDP)) or a proprietary protocol may be used for access point (AP) building classification in, for example, a campus network environment. Aspects of the presented techniques employ a modularity maximization-based community detection approach to classify the APs that reside within a building as a community. Further aspects of the techniques leverage protocol data to merge a network and create leaf nodes (representing APs), allowing the techniques to distinguish nodes that have no RSSI measurements from their neighboring nodes. Singular results from real world data demonstrate the effectiveness and scalability of the presented techniques.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Yazdanparast, Audrey; Amini, Peiman; Hart, Brian; Alizadeh, Ardalan; Kanak, Ather; and Schnorr, Nick, "ROBUST ACCESS POINT BUILDING CLASSIFICATION IN A CAMPUS NETWORK", Technical Disclosure Commons, (February 25, 2024)
https://www.tdcommons.org/dpubs_series/6713