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Compressive and cooperative sensing in distributed mobile sensor networks

机译:分布式移动传感器网络中的压缩和协作感测

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In this paper, we propose an algorithm to support distributed mobile sensors to collect data in sensing areas needing to be observed. The algorithm exploits random positions of mobile sensors to measure the area and applies compressive sensing (CS) to reconstruct all sensed data based on a certain number of CS measurements. At a time instant, the sensors add all readings within their sensing range and exchange their accumulative readings to their neighbors within a sensor communication range. Each CS measurement created at a time is a sum of all data measured by a group of connected sensors. We further analyze and formulate expression for power consumption for communications in the network. The measurement matrix, the number of mobile sensors, the sensing range and the communication range are analyzed and suggested for the networks to consume the least power.
机译:在本文中,我们提出了一种算法来支持分布式移动传感器,以收集在需要观察到的感测区域中的数据。该算法利用移动传感器的随机位置来测量该区域,并应用压缩感测(CS)以基于一定数量的CS测量来重建所有感测数据。在时间即时,传感器在其传感范围内添加所有读数,并在传感器通信范围内将其累积读数交换到邻居。一次创建的每个CS测量是由一组连接的传感器测量的所有数据的总和。我们进一步分析和制定了网络中通信的功耗的表达。分析测量矩阵,移动传感器的数量,感测范围和通信范围,并建议网络消耗最少的功率。

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