Abstract
The sensor data is heterogeneous, redundant, real-time, massive, streaming and is generated in high frequency. The increasing use of sensors leads to a rising demand on sensor data storage platforms. Appropriate data management is therefore, a key factor in making sure that the sensor data storage system becomes a reality. In this article we will focus on finding a data storage solution that is capable of storing huge amount of sensor data. The storage models in SQL and NoSQL databases are analyzed and compared, thus seeking an appropriate type of database for sensor data storage. Hypertable is identified to be the database that best suits the system requirements. It is therefore investigated how to implement the sensor data insertion and retrieval services. Query processing over distributed databases is more challenging than doing so in a centralized environment. Because NoSQL databases do not work with SQL, they require manual query programming which can be fast for simple tasks but time-consuming for others. This paper considers the extension of Hypertable query language with aggregate operations and describes the implementation of the query language interpreter.
Published Version
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