Enhanced quality of service in wireless sensor networks using cloud computing

Nowadays, wireless sensor network (WSN) applications have been used in several important areas, such as healthcare, military, environment, and industry. However, due to the limitations of WSNs in terms of memory, energy, computation, communication, and scalability, efficient management of the large number of WSNs data in these areas is an important issue to deal with. Traditional WSNs are used to perceive, collect and process information of the environmental in the network covered areas. Because of that the data collected is very big, previous data is deleted from databases in certain periods. This situation causes forward looking estimates to be in consistent and reports looking back to be received. In this scenario, cloud computing is becoming a promising technology to provide a flexible stack of massive computing, storage, and software services in a scalable and virtualized manner at low cost. In this thesis all measuring data can be stored on Microsoft SQL Azure cloud database without having a capacity problem. Measuring data can be used in different applications and various application platforms. The benefits of this system include basic computing hardware and reasonable storage capacities making it suitable for any smart device which can monitor real-time environmental information anywhere.