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Optimizing in-network aggregate queries in wireless sensor networks for energy saving

机译:优化无线传感器网络中的网络内聚合查询以节省能源

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This study proposes a method of in-network aggregate query processing to reduce the number of messages incurred in a wireless sensor network. When aggregate queries are issued to the resource-constrained wireless sensor network, it is important to efficiently perform these queries. Given a set of multiple aggregate queries, the proposed approach shares intermediate results among queries to reduce the number of messages. When the sink receives multiple queries, it should be propagated these queries to a wireless sensor network via existing routing protocols. The sink could obtain the corresponding topology of queries and views each query as a query tree. With a set of query trees collected at the sink, it is necessary to determine a set of backbones that share intermediate results with other query trees (called non-backbones). First, it is necessary to formulate the objective cost function for backbones and non-backbones. Using this objective cost function, it is possible to derive a reduction graph that reveals possible cases of sharing intermediate results among query trees. Using the reduction graph, this study first proposes a heuristic algorithm BM (standing for Backbone Mapping). This study also develops algorithm OOB (standing for Obtaining Optimal Backbones) that exploits a branch-and-bound strategy to obtain the optimal solution efficiently. This study tests the performance of these algorithms on both synthesis and real datasets. Experimental results show that by sharing the intermediate results, the BM and OOB algorithms significantly reduce the total number of messages incurred by multiple aggregate queries, thereby extending the lifetime of sensor networks.
机译:这项研究提出了一种网络内聚合查询处理方法,以减少无线传感器网络中出现的消息数量。当将聚合查询发布到资源受限的无线传感器网络时,有效执行这些查询很重要。给定一组多个聚合查询,建议的方法在查询之间共享中间结果以减少消息数量。当接收器收到多个查询时,应通过现有的路由协议将这些查询传播到无线传感器网络。接收器可以获取相应的查询拓扑,并将每个查询视为查询树。对于在接收器处收集的一组查询树,有必要确定一组与其他查询树共享中间结果的主干(称为非主干网)。首先,有必要制定骨干和非骨干的目标成本函数。使用该客观成本函数,可以得出一个简化图,该简化图揭示了在查询树之间共享中间结果的可能情况。本研究首先使用约简图提出一种启发式算法BM(代表骨干映射)。本研究还开发了算法OOB(代表获得最佳骨干),该算法利用分支定界策略有效地获得最佳解决方案。这项研究测试了这些算法在综合数据集和真实数据集上的性能。实验结果表明,通过共享中间结果,BM和OOB算法显着减少了多个聚合查询产生的消息总数,从而延长了传感器网络的寿命。

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