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Localized Delay-bounded and Energy-efficient Data Aggregation in low-traffic request-driven wireless sensor and actor networks

机译:低流量请求驱动的无线传感器和actor网络中的局部延迟限制和节能数据聚合

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We propose a localized Delay-bounded and Energy-efficient Data Aggregation scheme (DEDA) for wireless sensor and actor networks that are modeled as undirected graphs (URG). The scheme is based on a novel concept of Desired Hop Progress (DHP) and designed for low-traffic, request-driven network scenarios, where delay is proportional to hop count [10]. It builds a local minimal spanning tree (LMST) sub-graph of the network with links weighted by transmission powers. Using edges from LMST, it constructs a shortest path (thus energy-efficient) tree rooted at actor (sink) for data aggregation. The tree is used as is if it generates acceptable delay. Otherwise, it is adjusted by replacing LMST sub-paths with URG edges. The adjustment is done locally, according to the DHP value at each node, with hop count reduction corresponding to the delay allowance per hop (ratio of current LMST delay over maximal allowed one). Through extensive simulation, we show that DEDA may save 25–75% energy per node on average and extend up to 150% network life, depending on network conditions, in comparison with the only existing competing localized solution [11].
机译:我们为无线传感器和参与者网络提出了一种本地化的,有延迟限制的节能数据聚合方案(DEDA),该方案被建模为无向图(URG)。该方案基于所需跳数进度(DHP)的新颖概念,并设计用于低流量,请求驱动的网络场景,其中延迟与跳数成正比[10]。它建立网络的本地最小生成树(LMST)子图,并以传输功率加权链路。它使用来自LMST的边缘,构建了一个根植于参与者(接收器)的最短路径(因此具有能源效率)树,用于数据聚合。如果树产生可接受的延迟,则按原样使用它。否则,可以通过用URG边替换LMST子路径来进行调整。根据每个节点的DHP值,在本地进行调整,并减少跳数以对应于每跳的延迟允许(当前LMST延迟与最大允许延迟之比)。通过广泛的仿真,与唯一现有的竞争本地化解决方案相比,我们发现DEDA可以平均节省每个节点25-75%的能量,并可以根据网络条件延长网络寿命的150%(11)。

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