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Full-Text Articles in Computer Sciences
Experimental Evaluation Of Wireless Simulation Assumptions, David Kotz, Calvin Newport, Robert S. Gray, Jason Liu, Yougu Yuan, Chip Elliot
Experimental Evaluation Of Wireless Simulation Assumptions, David Kotz, Calvin Newport, Robert S. Gray, Jason Liu, Yougu Yuan, Chip Elliot
Dartmouth Scholarship
All analytical and simulation research on ad hoc wireless networks must necessarily model radio propagation using simplifying assumptions. We provide a comprehensive review of six assumptions that are still part of many ad hoc network simulation studies, despite increasing awareness of the need to represent more realistic features, including hills, obstacles, link asymmetries, and unpredictable fading. We use an extensive set of measurements from a large outdoor routing experiment to demonstrate the weakness of these assumptions, and show how these assumptions cause simulation results to differ significantly from experimental results. We close with a series of recommendations for researchers, whether …
The Changing Usage Of A Mature Campus-Wide Wireless Network, Tristan Henderson, David Kotz, Ilya Abyzov
The Changing Usage Of A Mature Campus-Wide Wireless Network, Tristan Henderson, David Kotz, Ilya Abyzov
Dartmouth Scholarship
Wireless Local Area Networks (WLANs) are now commonplace on many academic and corporate campuses. As “Wi-Fi” technology becomes ubiquitous, it is increasingly important to understand trends in the usage of these networks. \par This paper analyzes an extensive network trace from a mature 802.11 WLAN, including more than 550 access points and 7000 users over seventeen weeks. We employ several measurement techniques, including syslogs, telephone records, SNMP polling and tcpdump packet sniffing. This is the largest WLAN study to date, and the first to look at a large, mature WLAN and consider geographic mobility. We compare this trace to a …
Kerf: Machine Learning To Aid Intrusion Analysts, Javed Aslam, Sergey Bratus, David Kotz, Ron Peterson, Daniela Rus
Kerf: Machine Learning To Aid Intrusion Analysts, Javed Aslam, Sergey Bratus, David Kotz, Ron Peterson, Daniela Rus
Dartmouth Scholarship
Kerf is a toolkit for post-hoc intrusion analysis of available system logs and some types of network logs. It takes the view that this process is inherently interactive and iterative: the human analyst browses the log data for apparent anomalies, and tests and revises his hypothesis of what happened. The hypothesis is alternately refined, as information that partially confirms the hypothesis is discovered, and expanded, as the analyst tries new avenues that broaden the investigation.
Simulation Validation Using Direct Execution Of Wireless Ad-Hoc Routing Protocols, Jason Liu, Yougu Yuan, David M. Nicol, Robert S. Gray, Calvin C. Newport, David Kotz, Luiz Felipe Perrone
Simulation Validation Using Direct Execution Of Wireless Ad-Hoc Routing Protocols, Jason Liu, Yougu Yuan, David M. Nicol, Robert S. Gray, Calvin C. Newport, David Kotz, Luiz Felipe Perrone
Dartmouth Scholarship
Computer simulation is the most common approach to studying wireless ad-hoc routing algorithms. The results, however, are only as good as the models the simulation uses. One should not underestimate the importance of \em validation, as inaccurate models can lead to wrong conclusions. In this paper, we use direct-execution simulation to validate radio models used by ad-hoc routing protocols, against real-world experiments. This paper documents a common testbed that supports direct execution of a set of ad-hoc routing protocol implementations in a wireless network simulator. The testbed reads traces generated from real experiments, and uses them to drive direct-execution implementations …
Evaluating Location Predictors With Extensive Wi-Fi Mobility Data, Libo Song, David Kotz, Ravi Jain, Xiaoning He
Evaluating Location Predictors With Extensive Wi-Fi Mobility Data, Libo Song, David Kotz, Ravi Jain, Xiaoning He
Dartmouth Scholarship
Location is an important feature for many applications, and wireless networks can better serve their clients by anticipating client mobility. As a result, many location predictors have been proposed in the literature, though few have been evaluated with empirical evidence. This paper reports on the results of the first extensive empirical evaluation of location predictors, using a two-year trace of the mobility patterns of over 6,000 users on Dartmouth's campus-wide Wi-Fi wireless network. \par We implemented and compared the prediction accuracy of several location predictors drawn from two major families of domain-independent predictors, namely Markov-based and compression-based predictors. We found …