Robust and Secure Framework for Mobile Cloud Computing

Abstract

Smartphone devices are widely utilized in our daily lives. However, these devices exhibit limitations, like short battery lifetime, limited computation power, small memory size and unpredictable network connectivity. Therefore, various solutions have been projected to mitigate these limitations and extend the battery period of time with the employment of the offloading technique. In this paper, a unique framework is projected to offload intensive computation tasks from the mobile device to the cloud. This framework uses Associate in Nursing improvement model to work out the offloading decision dynamically supported four main parameters, namely, energy consumption, CPU utilization, execution time, and memory usage. Additionally, a new security layer is provided to shield the transferred data within the cloud from any attack. The experimental results showed that the framework will choose an acceptable offloading decision for various forms of mobile application tasks whereas achieving important performance improvement. Moreover, different from previous techniques, the framework will defend application knowledge from any threat.