A high-throughput path metric for multi-hop wireless routing
Proceedings of the 9th annual international conference on Mobile computing and networking
Routing in multi-radio, multi-hop wireless mesh networks
Proceedings of the 10th annual international conference on Mobile computing and networking
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Wireless Communications & Mobile Computing
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IEEE Pervasive Computing
Routing stability in static wireless mesh networks
PAM'07 Proceedings of the 8th international conference on Passive and active network measurement
Cross-layer resilience based on critical points in manets
Cross-layer resilience based on critical points in manets
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Principal Component Analysis (PCA) is a powerful method in data analysis. In this paper, we employ the capabilities of PCA combined with statistical fits to trace data to develop tractable models that can be used to simulate the quality of links in wireless mesh networks using the expected transmission time (ETT) metric. We apply principal component analysis to ETT traces from a wireless mesh network to determine what features in the ETT traces are important and to extract any meaningful relationships therein. We demonstrate that PCA can be used to efficiently approximate large volumes of ETT values. In particular, the ETT trace for each link can be expressed as a combination of two basis vectors -- one fairly stable and the other containing the variations in time. We also show how the extracted features can be employed to simulate ETT for a given network topology with and without known ETT trace data.