An Optimal Opportunistic Scheduling Algorithm for Parallel Tasks in a Cloudlet

With the development of Cloud Computing (CC) and mobile Internet, Mobile Cloud Computing (MCC) is becoming a new application mode. Mobile Cloud Computing allows cloudlet (i.e. a trusted computer which well-connected to the Internet and available for user to process the computational tasks) to access the nearby users' information for process at any time and any place. However, due to the mobility of the user and cloudlets, cloudlets may not be effectively control users information transmission. The PhD research work is mainly including the following four aspects: Firstly, we plan to calculate the effective range to ensure that the link between the users'mobile devices and the cloudlet in the whole task processing and transmission will not be interrupted. Secondly, since the cloudlet process tasks and transmission tasks need to consume energy, we discuss the minimum power cost problem as a time averaged optimization problem in order to save energy. Thirdly, we design two efficient algorithms by applying the Lyapunov optimization theory and virtual queue technology to ensure the cloudlet have an optimal scheduling strategy. Finally, we apply real-life power price to illustrate efficiency of our algorithms.