A framework for integrating wireless sensors and cloud computing

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 thesis 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. Finally, we present an eHealth smart system as a case study for collecting real-time data that can be used for real-time monitoring and data analysis.

Name thesis:degree_name

Master of Applied Science (MASc)

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

University of Ontario Institute of Technology

Year dc:date.issued

2015

Author dc:creator

• Jassas, Mohammad

Advisor dc:contributor.advisor

• Mahmoud, Qusay H.

• Cloud computing
• Wireless sensors
• Windows Azure
• Load testing

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/10155/598

OAI identifier oai:identifier

oai:ontariotechu.scholaris.ca:10155/598