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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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書(shū)目名稱Distributed Computing in Sensor Systems
副標(biāo)題5th IEEE Internation
編輯Bhaskar Krishnamachari,Subhash Suri,Urbashi Mitra
視頻videohttp://file.papertrans.cn/282/281862/281862.mp4
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Distributed Computing in Sensor Systems; 5th IEEE Internation Bhaskar Krishnamachari,Subhash Suri,Urbashi Mitra Conference proceedings 2009
描述The book constitutes the refereed proceedings of the Fifth International Conference on Distributed Computing in Sensor Systems, DCOSS 2009, 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, activity recognition, simulation, query optimization, network coding, localization, application development, data and code dissemination.
出版日期Conference proceedings 2009
關(guān)鍵詞Online; Scheduling; System; Transceiver; bandwith constrainted; cognition; communication; compressed stream
版次1
doihttps://doi.org/10.1007/978-3-642-02085-8
isbn_softcover978-3-642-02084-1
isbn_ebook978-3-642-02085-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2009
The information of publication is updating

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https://doi.org/10.1007/978-1-349-20680-3, it is often preferred to operate at a constant quality level as opposed to changing application behavior frequently. Reconciling the varying supply with the fixed demand requires good tools for predicting supply such that its average is computed and demand is fixed accordingly. In this paper, we d
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The Foundation of Japanese Powera streams in wireless multihop sensor networks is presented. Compact, necessary and sufficient closed-form solution to the optimal rate allocation problem is derived based on the lower rate approximation of rate distortion function. Extensive simulations were conducted using real-world data traces,
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