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引用次数: 0

摘要

传感器网络的移动性使用户能够有效地监测事先知之甚少的环境。例如,如果在森林中有一条可疑的路径应该被监控,但它的确切位置不知道,传感器可以分散在该区域,并在检测到人或动物时聚集在路径上。在这项工作中,我们提出了几种用于传感器的分布式算法来产生这种收敛。首先是开放矩形空间的稳健定位技术。我们也在此基础上生成了任意连通空间的算法。此外,我们还考虑了在运动中受到固有约束的传感器,例如固定在单线运动上的系绳传感器。我们提出了各种案例的分析和实证结果,并讨论了将提供更大效力的扩展
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Motion-constrained mobile sensor networks
The addition of mobility to sensor networks gives users the ability to efficiently monitor environments about which little is known ahead of time. For example, if there is a suspected path through the forest that should be monitored, but its exact location is not known, sensors can be scattered through the area and converge on the path as people or animals are detected on it. In this work, we present several distributed algorithms for sensors to produce this convergence. The first is a robust positioning technique for open rectangular spaces. We also build on this to produce an algorithm for arbitrary connected spaces. In addition, we consider sensors that are inherently constrained in their motion, such as tethered sensors fixed to a single line of motion. We present both analytical and empirical results for a variety of cases and discuss extensions that will provide greater effectiveness
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