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Interference mitigation and detection in wifi networks under congestion

University of British Columbia

In IEEE 802.11, nodes regulate access to the airspace they share in a decentralized fashion using CSMA/CA. The goal of this approach is to share the common airspace fairly and efficiently without requiring centralized channel administration or direct coordination among peer nodes. However, it is well known that strong interference, as consequence of this de-centralized coordination scheme, can lead to extremely unfair network bandwidth allocation between competing devices. Interference detection and mitigation has posed great challenges. The cause of interference is complicated, involving many networking factors such as topology and traffic, and the interference relationship changes all the time. This thesis addresses these challenges by proposing a throttling based interference mitigation system (Shaper) and an online passive interference detection system (VOID). The main contribution of this thesis is to point out the correlated relationship between interference and congestion. First, this thesis provides a more thorough analysis on the impact of node topology, traffic type and signal strength on wireless performance. We came up with 9 UDP models and 10 TCP models just for two competing flow scenarios. The outcome of wireless interference can get harder to predict, however, as we introduce more factors into the interference model such as more competing nodes, sending rate, signal propagation model, etc. On the other hand, this thesis identifies the immediate cause to the unfair bandwidth distribution under interference: 802.11 network congestion. We observed and explained that all competing devices are able to perform well regardless of topology or traffic class, as long as there is sufficiently more bandwidth than the aggregate throughput demands. Therefore, we propose to trade the aggregate throughput to mitigate the impact of interference and prove its effectiveness through simulation and emulation. Finally, the key to successful addressing the interference is an accurate and fast interference detection mechanism and this thesis proposes such a system called VOID. It deploys the correlation between congestion and interference to infer the interference relationship from the ip-layer throughput variations. It is fast, accurate and more importantly, very easy to deploy in existing WiFi networks.

Text

2015-06-17

Attribution-NonCommercial-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/53933

Computer Science

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/