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In order for wireless sensor networks to exploit signal, signal data must be collected at a multitude of sensors and must be shared among the sensors. The vast sharing of data among the sensors contradicts the requirements (energy efficiency, low latency and high accuracy) of wireless networked sensor. This paper describes the design and implementation of the two lossless data compression algorithms integrated with the shortest path routing technique to reduce the raw data size and to accomplish optimal trade-off between rate, energy, and accuracy in a sensor network. To validate and evaluate the work, the author applies it to different types of datasets from different real-world deployments and show that the approaches can reduce energy consumption over other data compression schemes based on simulations.
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