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Algorithms for bounding end-to-end delays in Wireless Sensor Networks

机译:无线传感器网络中的端到端延迟限制算法

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Wireless Sensor Networks (WSNs) have many characteristics that are attractive to a myriad of applications. In particular, nodes employ multi-hop communications to collaboratively forward sensed data back to one or more sinks. In this context, reducing the end-to-end delay between the sink and sensor/source nodes is of interest to many applications. In particular, those that require a fixed, upper bound on end-to-end delays. To this end, we focus on bounding the end-to-end delay from the sink to each source. We first formulate the problem as a Binary Integer Program (BIP). As the problem is NP-hard, this paper proposes and studies two centralized, heuristic algorithms: Tabu and Domino. The key approach used by both algorithms is to determine the minimal number of extra wake-up slots required by a given network in order to ensure the delay of all end-to-end paths is within a given bound. We conducted two sets of experiments. The first set compares BIP, Tabu, and Domino in WSNs with up to 80 nodes. These experiments serve to compare the proposed algorithms against BIP, which become computationally expensive in large scale WSNs. The results show that, compared to BIP, the number of additional wake-up times generated by Tabu and Domino are within 5 and 10 % of the optimal solution. In the second set of experiments, which evaluates the algorithms in WSNs with 100-500 nodes, the average number of extra wake-up slots activated by Domino is 13 % greater than Tabu. These algorithms have a time complexity of O(αn~2T + n~3) and O(n~3) respectively, where n is the number of nodes, T is the number of slots in one period, and α is the maximum number of iterations carried out by the Tabu algorithm.
机译:无线传感器网络(WSN)具有许多吸引众多应用程序的特性。特别地,节点采用多跳通信以将感测的数据协作地转发回一个或多个接收器。在这种情况下,减少接收器和传感器/源节点之间的端到端延迟是许多应用所关注的。特别是那些需要固定的端到端延迟上限的延迟。为此,我们专注于限制从接收器到每个源的端到端延迟。我们首先将问题表述为二进制整数程序(BIP)。由于问题是NP难题,因此提出并研究了两种集中式启发式算法:Tabu算法和Domino算法。两种算法使用的关键方法是确定给定网络所需的最少额外唤醒时隙数,以确保所有端到端路径的延迟都在给定范围内。我们进行了两组实验。第一组比较WSN中最多有80个节点的BIP,禁忌和Domino。这些实验用于将提出的算法与BIP进行比较,而BIP在大规模WSN中变得计算量大。结果表明,与BIP相比,Tabu和Domino产生的额外唤醒时间在最佳解决方案的5%和10%之内。在第二组实验中,该实验评估了具有100-500个节点的WSN中的算法,Domino激活的额外唤醒时隙的平均数量比Tabu大13%。这些算法的时间复杂度分别为O(αn〜2T + n〜3)和O(n〜3),其中n是节点数,T是一个周期中的时隙数,α是最大数禁忌算法执行的迭代次数。

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