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Stream engines meet wireless sensor networks:cost-based planning and processing of complex queries in AnduIN

机译:流引擎满足无线传感器网络的需求:基于成本的计划和AnduIN中复杂查询的处理

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Wireless sensor networks are powerful, distributed, self-organizing systems used for event and environmental monitoring. In-network query processors like TinyDB offer a user friendly SQL-like application development. Due to the sensor nodes' resource limitations, monolithic approaches often support only a restricted number of operators. For this reason, complex processing is typically outsourced to the base station. Nevertheless, previous work has shown that complete or partial in-network processing can be more efficient than the base station approach. In this paper, we introduce AnduIN, a system for developing, deploying, and running complex in-network processing tasks. In particular, we present the query planning and execution strategies used in AnduIN, a system combining sensor-local in-network processing and a data stream engine. Query planning employs a multi-dimensional cost model taking energy consumption into account and decides autonomously which query parts will be processed within the sensor network and which parts will be processed at the central instance.
机译:无线传感器网络是用于事件和环境监控的强大,分布式,自组织系统。诸如TinyDB之类的网络内查询处理器提供了用户友好的类似SQL的应用程序开发。由于传感器节点的资源限制,单片方法通常仅支持有限数量的操作员。因此,通常将复杂的处理工作外包给基站。但是,先前的工作表明,完整或部分的网络内处理可能比基站方法更有效。在本文中,我们介绍了AnduIN,这是一个用于开发,部署和运行复杂的网络内处理任务的系统。特别是,我们介绍了AnduIN中使用的查询计划和执行策略,该系统结合了传感器本地网络内处理和数据流引擎。查询计划采用了多维成本模型,其中考虑了能耗,并自主决定了哪些查询部件将在传感器网络内进行处理以及哪些部件将在中央实例处进行处理。

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