In this paper, we study the problem of opportunistic task scheduling and workload management in a mobile cloud setting consid- ering computation power variation. We gathered mobile usage data for a number of persons and applied supervised clustering to show that a pattern of usage exists and that follows a state-based model. Based on this model, we present a strategy to choose and offload work on a mobile device. We present a framework and experimental results showing the efficacy of our proposed approach.
['Ansuman Banerjee', 'Himadri Sekhar Paul', 'Arijit Mukherjee', 'Swarnava Dey', 'Pubali Datta']
A Framework for Speculative Scheduling and Device Selection for Task Execution on a Mobile Cloud