An Efficient Scheduling Strategy in Mobile Cloud: Model and Algorithm
Mobile cloud computing can balance the application distribution between the mobile device and the cloud, in order to achieve faster interactions, battery savings and better resource utilization. The paper considers batch processing applications for mobile cloud computing environment. The mobile device’s user requirements arrive in batches into the mobile cloud systems. For example, mobile device’s users submit batch jobs (e.g., financial analytics, scientific simulations) to mobile cloud system for fast processing. The paper proposes a phased scheduling model of mobile cloud such that mobile device’s users experience lower interaction times and extended battery life. The phased scheduling optimization is solved by two subproblems: mobile device’s batch application optimization and mobile device’s job level optimization. At the first stage, the mobile cloud global scheduling optimization implements the allocation of the cloud resources to the mobile device’s batch applications. At the second stage, mobile device’s job level optimization adjusts the cloud resource usages to optimize the utility of single mobile device’s application. In the simulations, compared with other algorithm, our proposed mobile cloud phased scheduling algorithms achieve the better performance with acceptable overhead.