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Tandem: A Context-Aware Method forSpontaneous Clustering of Dynamic Wireless Sensor Nodes

机译:串联:动态无线传感器节点自发聚类的上下文感知方法

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Wireless sensor nodes attached to everyday objects and worn by people are able to collaborate and actively assist users in their activities. We propose a method through which wireless sensor nodes organize spontaneously into clusters based on a common context. Provided that the confidence of sharing a common context varies in time, the algorithm takes into account a window-based history of believes. We approximate the behaviour of the algorithm using a Markov chain model and we analyse theoretically the cluster stability. We compare the theoretical approximation with simulations, by making use of experimental results reported from field tests. We show the tradeoff between the time history necessary to achieve a certain stability and the responsiveness of the clustering algorithm.
机译:附着在日常物品上并由人们佩戴的无线传感器节点能够协作并积极协助用户进行活动。我们提出了一种方法,通过该方法,无线传感器节点可以基于公共上下文自发地组织为群集。假设共享公共上下文的置信度随时间变化,则该算法将考虑基于窗口的信念历史。我们使用马尔可夫链模型对算法的行为进行近似,并从理论上分析集群的稳定性。通过利用现场测试报告的实验结果,我们将理论逼近与仿真进行了比较。我们展示了在达到一定稳定性所需的时间历史与聚类算法的响应能力之间的权衡。

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