Enhancement of the Dynamic Computation-Offloading Service Selection Framework in Mobile Cloud Environment

In the era of cloud computing, any mobile device can augment its capabilities by using Cloud computation service. There are different services provided by different cloud service providers. The mobile device has to access the cloud service with minimum response time. So many a times, instead of a distant cloud, nearest cloudlet is chosen to access the service. But according to the mobility of the user, choosing the right service provider is a herculean task. Hence this paper suggests a framework to choose a cloudlet service provider in a multi-user computation offloading environment and accommodate the service that is adaptive based on the movement of the mobile device. This paper defines a framework which comprises of basically two components. The foremost one is Fuzzy KNN component which classifies the mobile device based on the access range of the device with a nearby cloudlet. The later component provides a dynamic service depending on the changes in the mobile device location. The framework exploits Fuzzy K nearest neighbour (KNN) and Hidden Markov Model to enhance the Dynamic computation-offloading service selection (EDCOSS) framework. The EDCOSS framework is analysed and tested in a simulation environment to verify the efficiency of the framework in terms of convergence of the algorithm towards computation cost with respect to different number of clients and communication channels.