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Optimization of Actors Placement in WSANs based on Imposed Delay Constraints

机译：基于强加延迟约束的WSAN中Actor布局的优化

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Wireless Sensor and Actor Networks (WSANs) refer to a group of sensors and actors linked by wireless medium to probe environment and perform specific actions.These actions should be taken before an established deadline when an event of interest is detected.According to the relationship between the end-to-end delay and the number of hops for sensed data passing through,the size of the WSANs cluster should be limited.In this paper,we find a method to determine the maximum size of the WSANs cluster which enables the cluster-head to receive data and take actions in an imposed time-delay.For clustering of the WSANs,a k-MTE clustering algorithm is proposed which is inspired by the regular six-polygon deployment.In this algorithm,actors are employed as cluster-heads and placed in such a way that sensors could route data to actors within k hops.The maximum size of k-MTE based cluster is determined by statistical analysis of simulation experiments and thus the number of actors needed to cover a certain area can be determinate.At last,we evaluate the placement of actors and the results show that our approach is effective.
机译：无线传感器和参与者网络（WSAN）是指通过无线介质链接以探测环境并执行特定操作的一组传感器和参与者，这些操作应在检测到感兴趣事件的既定期限之前采取。 WSAN群集的大小应受到限制，端到端的延迟和所感测数据通过的跳数应受到限制。在本文中，我们找到了一种确定WSAN群集的最大大小的方法，该方法使群集能够-对于WSAN的聚类，提出了一种k-MTE聚类算法，该算法受常规六多边形部署的启发。在WSAN的聚类中，actor被用作聚类头。并以使传感器可以将数据路由到k跳内的参与者的方式放置。基于k-MTE的群集的最大大小是通过对模拟实验进行统计分析来确定的，因此需要一个参与者的数量来覆盖一个最后，我们评估了演员的位置，结果表明我们的方法是有效的。

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