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Distributed Real-Time Data Aggregation Scheduling in Duty-Cycled Multi-hop Sensor Networks

机译:占空比多跳传感器网络中的分布式实时数据聚合调度

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Wireless sensor network (WSN) systems often need to support real time periodic queries of physical environments. In this work, we focus on periodic queries with sufficiently long time horizon in duty-cycled sensor networks. For each periodic query issued by a control center in a WSN, after the source sensors produced the sensory data, the data are to be sent to the sink via multi-hop data aggregation timely in a periodic fashion. To this end, we propose efficient and effective data aggregation algorithms subject to quality of service constraints such as deadline requirements and interference constraints. We decompose these into three sequential operations: (1) aggregation tree construction (2) node and link-level scheduling and (3) packet scheduling. Inspired by the scheduling algorithms, we identify both sufficient conditions and necessary conditions for scheduling multiple queries. The schedulability analysis under various interference models demonstrate that the proposed algorithms achieve an approximate proportion of the maximum possible load.
机译:无线传感器网络(WSN)系统通常需要支持物理环境的实时定期查询。在这项工作中,我们重点研究占空比传感器网络中具有足够长时间范围的定期查询。对于WSN中控制中心发出的每个定期查询,在源传感器生成感官数据之后,数据将通过多跳数据聚合以周期性的方式及时发送到接收器。为此,我们提出了有效且有效的数据聚合算法,该算法受服务质量约束(例如,期限要求和干扰约束)的约束。我们将它们分解为三个顺序的操作:(1)聚合树构建(2)节点和链路级调度以及(3)数据包调度。受调度算法的启发,我们确定了调度多个查询的充分条件和必要条件。在各种干扰模型下的可调度性分析表明,所提出的算法实现了最大可能负载的近似比例。

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