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This paper studies the scaling law of the data gathering capacity of large-scale wireless sensor networks. Many previous researches on data gathering capacity focus on a many-to-one scheme, but we study the capacity in a multi-session data gathering paradigm, where some of the nodes in the network act as sinks and each sink has a set of source nodes to collect data. The analysis of this paradigm is...
In this paper, we propose a novel idea to perform efficient data processing in low-power wireless networks under noisy environments. We provide intuitions from compressed sensing about how to go about processing information accurately or near accurately in lossy environments. We show the way to future wireless network researchers about harnessing the tremendous power of compressed sensing in various...
This paper firstly introduces the compressed sensing theory that is very hot in recent research. Our research combines the compressed sensing with wireless sensor network to improve the prior classical formulas due to the great advantage of capabilities of compressing data in large scale wireless network. When the transmission data decrease sharply, the throughput increases obviously in our research...
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