面向物联网海量传感器采样数据管理的数据库集群系统框架

A Database Cluster System Framework for Managing Massive Sensor Sampling Data in the Internet of Things

物联网是目前国际和国内新兴的一项热门技术,正在给人们的生产和生活方式带来深刻的变革.物联网在带来诸多好处的同时,也给软件乃至整个信息技术领域带来了前所未有的挑战.该文针对物联网传感器采样数据管理中所面临的数据海量性、异构性、时空敏感性、动态流式特性等问题,提出一种面向物联网海量传感器采样数据管理的数据库集群系统框架IoT-ClusterDB.实验结果表明,IoT-ClusterDB具有良好的传感器数据接入与查询处理性能,为物联网海量异构传感器采样数据的存储与查询处理提供了一种可行的解决方案.

In recent years, the Internet of Things （IoT） has become increasingly important and is changing the way how people live and work. IoT has a lot of benefits and meanwhile, it also brings about great challenges to the software and the whole IT community. In this paper, we mainly focus on the challenges in IoT data management. In IoT systems, the data sampled from sensors are massive and heterogeneous. Besides, they are spatial-temporal and dynamically changing stream data. To meet these challenges, we propose an IoT Database Cluster System Framework for Managing Massive Sensor Sampling Data （IoT-ClusterDB） in this paper. The experimental results show that IoT-ClusterDB has satisfactory sensor data uploading and query processing performances and thus provides a good solution for managing and querying massive sensor data in the Internet of Things.