Authors: Mohammad S. Jassas; Qusay H. Mahmoud
Addresses: Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology, Oshawa, ON, L1H 7K4, Canada ' Department of Electrical, Computer and Software Engineering, University of Ontario Institute of Technology, Oshawa, ON, L1H 7K4, Canada
Abstract: Wireless sensors generate a large volume of data that require a highly scalable framework that enables storage, processing, and analysis. Cloud computing technology can provide unlimited storage in addition to a flexible processing infrastructure, allowing for the management and analysis of vast amounts of sensor data. This paper presents a framework for integrating wireless sensors and cloud computing. This framework can provide scalability and high availability for applications that use wireless sensors. Moreover, this cloud-based framework is designed to immediately make decisions based on real-time sensor and historical data, and a list of sensor and user policies are defined by the system administrator. In order to evaluate the framework performance after applying scalability and availability techniques, a load testing environment was built in the cloud to simulate a large number of virtual users. This environment was created in order to examine the quality of the services as provided by Windows Azure. The results have shown that the use of scalability techniques can significantly increase availability and performance.
Keywords: cloud computing; wireless sensor networks; WSNs; Raspberry Pi; Windows Azure.
International Journal of Cloud Computing, 2017 Vol.6 No.2, pp.95 - 124
Received: 09 Mar 2016
Accepted: 31 Mar 2016
Published online: 09 Aug 2017 *