CAJ | 학술논문

在智慧城市中传感器和设备收集各种数据，实现增值服务。主要关注来自智慧城市中的智能房屋数据，提出用于存储和处理大规模房屋数据的Scallop4SC平台，实现智慧城市服务。房屋数据分为房屋日志数据和房屋配置数据，分别使用HBase和MYSQL管理。通过HBase键值以schemaless方式存储管理异构日志数据。 MySQL管理配置数据，完成房屋数据查询。多节点 Hadoop/MapReduce 集群处理巨量房屋日志数据。最后通过实际一年的房屋日志数据，计算智能设备能耗并完成实验性评估。根据实验结果，探讨Scallop4SC处理智慧城市的数据规模。
재지혜성시중전감기화설비수집각충수거，실현증치복무。주요관주래자지혜성시중적지능방옥수거，제출용우존저화처리대규모방옥수거적Scallop4SC평태，실현지혜성시복무。방옥수거분위방옥일지수거화방옥배치수거，분별사용HBase화MYSQL관리。통과HBase건치이schemaless방식존저관리이구일지수거。 MySQL관리배치수거，완성방옥수거사순。다절점 Hadoop/MapReduce 집군처리거량방옥일지수거。최후통과실제일년적방옥일지수거，계산지능설비능모병완성실험성평고。근거실험결과，탐토Scallop4SC처리지혜성시적수거규모。
In the smart city environment, a wide variety of data are collected from sensors and devices to achieve value-added services. In this paper, we especially focus on data taken from smart houses in the smart city, and propose a platform, called Scallop4SC, that stores and processes the large-scale house data. The house data is classified into log data or configuration data. Since the amount of the log is extremely large, we introduce the Hadoop/MapReduce with a multi-node cluster. On top of this, we use HBase key-value store to manage heterogeneous log data in a schemaless manner. On the other hand, to manage the configuration data, we choose MySQL to process various queries to the house data efficiently. We propose practical data models of the log data and the configuration data on HBase and MySQL, respectively. Then we show how Scallop4SC works as an efficient data platform for smart city services. We conduct an experimental evaluation to calculate device-wise energy consumption, using actual house log recorded for one year in our smart house. Based on the result, we discuss the applicability of Scallop4SC to city-scale data processing.