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Recent research on Internet traffic classification algorithms has yield a flurry of proposed approaches for distinguishing types of traffic, but no systematic comparison of the various algorithms. This fragmented approach to traffic classification research leaves the operational community with no basis for consensus on what approach to use when, and how to(More)
Domain name system (DNS) is a primary identification mechanism for Internet applications. However, DNS resolutions often take an unbearably long time, and this could seriously impair the consistency of the service quality of Internet applications based on DNS such as World Wide Web. Several approaches reduce DNS resolution time by proactively refreshing(More)
—Monitoring network traffic and classifying applications are essential functions for network administrators. In this paper, we consider the use of Traffic Dispersion Graphs (TDGs) to classify network traffic. Given a set of flows, a TDG is a graph with an edge between any two IP addresses that communicate; thus TDGs capture network-wide interactions. Using(More)
Recent research on Internet traffic classification has yield a number of data mining techniques for distinguishing types of traffic, but no systematic analysis on "Why" some algorithms achieve high accuracies. In pursuit of empirically grounded answers to the "Why" question, which is critical in understanding and establishing a scientific ground for traffic(More)
Recent research on Internet traffic classification has produced a number of approaches for distinguishing types of traffic. However, a rigorous comparison of such proposed algorithms still remains a challenge, since every proposal considers a different benchmark for its experimental evaluation. A lack of clear consensus on an objective and cientific way for(More)
Monitoring network traffic and detecting emerging P2P applications is an increasingly challenging problem since new applications obfuscate their traffic. Despite recent efforts, the problem is not yet solved and network administrators are still looking for effective and deployable tools. In this paper, we address this problem using Traffic Dispersion Graphs(More)
The human arm has 7 degrees of freedom (DOF) while only 6 DOF are required to position the wrist and orient the palm. Thus, the inverse kinematics of an human arm has a nonunique solution. Resolving this redundancy becomes critical as the human interacts with a wearable robot and the inverse kinematics solution of these two coupled systems must be identical(More)
Monitoring network traffic and classifying applications are essential functions for network administrators. Current traffic classification methods can be grouped in three categories: (a) flow-based (e.g., packet sizing/timing features), (b) payload-based, and (c) host-based. Methods from all three categories have limitations, especially when it comes to(More)
The human arm including the shoulder, elbow, wrist joints and exclusion scapular motion has 7 Degrees of Freedom (DOF) while positioning of the wrist in space and orientating the palm is a task that requires 6 DOF. As such it includes one more DOF than is needed to complete the task. Given the redundant nature of the arm, multiple arm configurations can be(More)
We conduct comprehensive measurements on the current practice of content bundling to understand the structural patterns of torrents and the participant behaviors of swarms on one of the largest BitTorrent portals: The Pirate Bay. From the datasets of the 120K torrents and 14.8M peers, we investigate what constitutes torrents and how users participate in(More)