An integrated framework for managing massive and heterogeneous sensor data using cloud computing

Abstract

Cloud computing can provide a powerful, scalable storage and the massive data processing infrastructure to perform both online and offline analysis and mining of the heterogeneous sensor data streams. With the recent explosion of wireless sensor networks and their applicability in military and civilian applications, there is an emerging vision for integrating sensor networks into the cloud computing platform. In contrast to traditional data objects, the sensor data objects have continuously changed, high-dimensional, spatiotemporal relation and heterogeneous attributes. Therefore, the management and processing problem of the massive sensor data objects can be more complicated. The paper formally presents an integrated framework for managing massive and heterogeneous sensor data with insights into the high-dimensional problem using the map-reduce platform of cloud computing. The proposed framework incorporates key concepts such as parallel-processing, scalability and flexibility of resources, sensor data uncertainty and the dynamic deployment and management of applications.