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Parallel Processing of Sensor Network Data using Column-Oriented Databases

机译:使用面向列的数据库并行处理传感器网络数据

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摘要

Many wireless sensor network (WSN) applications require join of sensor data belonging to various sensor nodes. For join processing, it is important to minimize the communication cost since it is the main consumer of battery power. In this paper, we introduce a parallel join technique for sensor networks. A WSN consists of many independent sensor nodes and provides a natural platform for a shared-nothing architecture to carry out parallel processing. The proposed parallel join algorithm is based on sensor data that are stored in column-oriented databases. A column-oriented database store table data column-wise rather than row-wise as in traditional relational databases. The proposed algorithm is energy-efficient for two clear reasons. First, unlike relational databases, only relevant columns are shipped to the join region for final join processing. Second, parallel join processing of sensor data also improves performance. The performance analysis shows that the proposed algorithm outperforms join algorithms for sensor data that are based on relational databases.
机译:许多无线传感器网络(WSN)应用需要连接属于各种传感器节点的传感器数据。为了加入处理,重要的是要最大限度地减少通信成本,因为它是电池电量的主要消费者。在本文中,我们引入了传感器网络的并行连接技术。 WSN由许多独立的传感器节点组成,为共享架构提供自然平台,以执行并行处理。所提出的并行连接算法基于存储在面向列的数据库中的传感器数据。面向列的数据库存储表数据列 - 方向而不是传统关系数据库中的卷。提出的算法是节能的两种明确原因。首先,与关系数据库不同,只有相关列已运送到连接区域以进行最终连接处理。其次,并行连接处理传感器数据也提高了性能。性能分析表明,所提出的算法优于基于关系数据库的传感器数据的连接算法。

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