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We present an efficient anomaly detection algorithm, named BANBAD. Using belief networks (BNs), the algorithm identifies abnormal behavior, like inappropriate energy consumption, in mobile ad-hoc networks (MANETs). By applying structure learning techniques to training dataset, BANBAD extracts the dependencies among relevant features, such as average velocity, displacement, local computation and communication...
Cross layer optimizations are increasingly being used in a variety of applications to improve application performance. However most of these implementations are ad hoc and performed on a per application basis. In this paper we propose a declarative framework for managing application and network adaptations. The declarative paradigm provides a much needed clean line of separation between the high level...
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