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首页> 外文期刊>Journal of Parallel and Distributed Computing >Spreading Aggregation: A distributed collision-free approach for data aggregation in large-scale wireless sensor networks
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Spreading Aggregation: A distributed collision-free approach for data aggregation in large-scale wireless sensor networks

机译：扩展聚合：一种用于大型无线传感器网络中数据聚合的分布式无冲突方法

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Recently, numerous works have shown that serial aggregation in large wireless sensor networks is scalable and very efficient, in terms of avoiding collisions and conserving energy and, more importantly, in terms of reducing response time. In this paper, a novel serial data aggregation approach, called Spreading Aggregation (SA), is proposed with the aim of shortening the traversal path and further reducing communications. First, given the fact that it is not based on a pre-established itinerary, SA is data structure maintenance-free and does not require any communications in this regard. Each time an aggregation process is launched, a new path is built, which decreases vulnerability to failure in links and nodes and allows the approach to handle topology changes. Second, SA is a localized approach that relies only on the one-hop neighbors table of each node to gradually construct the path, which makes it very scalable. A third interesting feature of SA is the merge of path construction and data processing. While the path is progressively constructed, data is simultaneously aggregated, saving a considerable amount of time and energy. In addition to all that, SA also saves energy and time due to its collision-free nature. In fact, in SA, only one packet is present in the entire network at any given time. In this paper, we formally prove the correctness of SA (i.e., free of looping and ensures the traversal of all connected nodes). Furthermore, the extensive OMNeT++ simulations, we performed, confirm that the proposed approach reduces communications, scales well in large networks, and conserves time and energy. The obtained results also show that SA outperforms state-of-the-art serial approaches. (C) 2018 Elsevier Inc. All rights reserved.
机译：近来，许多工作表明，在避免冲突和节省能量方面，更重要的是，在减少响应时间方面，大型无线传感器网络中的串行聚合是可扩展的并且非常有效。为了缩短遍历路径并进一步减少通信量，本文提出了一种新的串行数据聚合方法，称为扩频聚合（SA）。首先，考虑到它不是基于预先确定的路线，因此SA是无需维护数据结构的，因此在这方面不需要任何通信。每次启动聚合过程时，都会建立一条新路径，这会减少链路和节点发生故障的脆弱性，并允许该方法处理拓扑更改。其次，SA是一种本地化方法，它仅依赖于每个节点的单跳邻居表来逐步构建路径，这使其具有很高的可伸缩性。 SA的第三个有趣特征是路径构造和数据处理的合并。在逐步构建路径的同时，将同时汇总数据，从而节省大量时间和精力。除此之外，SA还具有无碰撞的特性，还可以节省能源和时间。实际上，在SA中，任何给定时间在整个网络中仅存在一个数据包。在本文中，我们正式证明了SA的正确性（即无循环并确保遍历所有连接的节点）。此外，我们进行了广泛的OMNeT ++仿真，证实了所提出的方法减少了通信，在大型网络中很好地扩展，并节省了时间和精力。获得的结果还表明，SA的表现优于最新的串行方法。 （C）2018 Elsevier Inc.保留所有权利。

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