- Electrical and Electronic Engineering - Research Publications
Electrical and Electronic Engineering - Research Publications
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ItemAn efficient resource allocation algorithm for OFDMA-based multihop wireless transmissionChen, L ; Krongold, B (IEEE, 2007-12-01)
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ItemAn efficient self-healing process for ZigBee sensor networksQiu, W ; Hao, P ; Evans, RJ (IEEE, 2007-01-01)
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ItemThe Cost of VariabilityRidoux, J ; Veitch, D (IEEE, 2008-01-01)
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ItemSubspace-based Methods for Crosstalk Cancellation in OFDM SystemsQiu, W ; Skafidas, E (IEEE, 2008-01-01)
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ItemRouting and Localization for Extended Lifetime in Data Collection Wireless Sensor NetworksQiu, W ; Pham, M ; Skafidas, E (Institute of Electrical and Electronics Engineers (IEEE), 2008-01-01)
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ItemPerformance Evaluation of Optical OFDM Systems with Nonlinear Clipping DistortionChen, L ; Krongold, B ; Evans, J (IEEE, 2009-01-01)
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ItemCounter availability and characteristics for feed-forward based synchronizationBroomhead, T ; Ridoux, J ; Veitch, D (IEEE, 2009-12-18)
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ItemImproving the fairness of FAST TCP to new flowsCui, T ; Andrew, LLH ; Zukerman, M ; Tan, L (IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2006-05-01)
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ItemPrinciples of Robust Timing over the InternetRidoux, J ; Veitch, D (ASSOC COMPUTING MACHINERY, 2010-05-01)The key to synchronizing clocks over networks is taming delay variability.
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ItemElliptical Anomalies in Wireless Sensor NetworksRajasegarar, S ; Bezdek, JC ; Leckie, C ; Palaniswami, M (ASSOC COMPUTING MACHINERY, 2009-12-01)Anomalies in wireless sensor networks can occur due to malicious attacks, faulty sensors, changes in the observed external phenomena, or errors in communication. Defining and detecting these interesting events in energy-constrained situations is an important task in managing these types of networks. A key challenge is how to detect anomalies with few false alarms while preserving the limited energy in the network. In this article, we define different types of anomalies that occur in wireless sensor networks and provide formal models for them. We illustrate the model using statistical parameters on a dataset gathered from a real wireless sensor network deployment at the Intel Berkeley Research Laboratory. Our experiments with a novel distributed anomaly detection algorithm show that it can detect elliptical anomalies with exactly the same accuracy as that of a centralized scheme, while achieving a significant reduction in energy consumption in the network. Finally, we demonstrate that our model compares favorably to four other well-known schemes on four datasets.