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Reliable continuous objects detection algorithm in wireless sensor networks

机译:无线传感器网络中可靠的连续对象检测算法

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In wireless sensor networks, reliable event detection is one of the most important research issues. For the reliable event detection, existing studies usually assume that events are individual objects such as tanks, people, and animals. The existing studies estimate detection reliability of an individual object by the ratio of the number of successfully received data packets at a sink to the number of data packets determined by applications for reliable detection. Recently, detection of the other one kind of events, called the continuous object, such as wild fire and bio-chemical material has been receiving increased attention. Unlike the individual objects, a continuous object might cover a wide area and it could dynamically alter its own shape according to physical environments, e.g. wind, geographical features, and so on. Hence, the continuous object detection reliability can not be estimated by the indicator for the individual objects. In this paper we newly define the reliability indicator for continuous object detection. Then, we propose error recovery and revision scheme based on the estimation result from the novel indicator. Simulation results prove that the proposed scheme provides high reliability with respect to continuous object detection.
机译:在无线传感器网络中,可靠的事件检测是最重要的研究问题之一。对于可靠的事件检测,现有研究通常假设事件是坦克,人类和动物等单独物体。现有研究通过在接收器中成功接收的数据分组的数量的比率来估计单个对象的检测可靠性,以通过应用于可靠检测的应用程序确定的数据分组的数量。最近,检测另一种事件,称为连续对象,例如野火和生物化学材料已经受到增加的关注。与单个对象不同,连续对象可能覆盖广域,可以根据物理环境动态改变其自己的形状,例如,风,地理特征等。因此,不能由各个对象的指示符估计连续对象检测可靠性。在本文中,我们新定义了连续对象检测的可靠性指示。然后,我们提出了基于新型指示符的估计结果的错误恢复和修订方案。仿真结果证明了所提出的方案对连续对象检测提供了高可靠性。

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