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Titlebook: Distributed Computing in Sensor Systems; 5th IEEE Internation Bhaskar Krishnamachari,Subhash Suri,Urbashi Mitra Conference proceedings 2009

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楼主: 恶化
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Energy Adaptive Sensor Scheduling for Noisy Sensor Measurements,ved by dynamic programming and one-step-look-ahead methods. Simulation results are presented to evaluate the performance of both methods. The dynamic programming method produced better results with higher computational cost than the one-step-look-ahead method.
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MCP: An Energy-Efficient Code Distribution Protocol for Multi-Application WSNs,ed to broadcasting based schemes, MCP greatly reduces signal collision and saves both the dissemination time and reduces the number of dissemination messages. Our experiments results show that MCP can reduce dissemination time by 25% and message overhead by 20% under various network settings.
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0302-9743 held in Marina del Rey, CA, USA, in June 2009. The 26 revised full papers presented were carefully reviewed and selected from 116 submissions. The research contributions in this proceedings span many aspects of sensor systems, including energy efficient mechanisms, tracking and surveillance, activit
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The Foundation of Japanese Powerwly, produce distorted estimates, or suffer large transients. The CRF-Gradient algorithm[1] addresses these shortcomings, and in this paper we prove that it self-stabilizes in .(.) time—more specifically, in 4 ·./. + . seconds, where . is a small constant and . is the minimum speed of multi-hop message propagation.
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The Class , of Degrees of Unsolvabilityn. We analyze and optimize coding parameters and present the design and evaluation of RTOC, a protocol for bulk transport that recovered over 95% of application data despite up to 84% packet loss in a MicaZ network.
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The Foundations of Computability Theoryor network. We also present decentralized techniques which allow monitoring and data analysis to be performed cooperatively by the nodes. The simplicity of our approach makes it attractive for sensor networks. Experiments with simulated and real data demonstrate the capabilities of the approach in both centralized and decentralized scenarios.
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The Class , of Degrees of Unsolvabilityor monitoring traffic is (.) inexpensive, (.) rapidly deployable, and (.) requires minimal maintenance. We report on our experiences in building this system, and with testing our system in live work zones in the Cleveland area.
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