Minimizing Execution Cost of User Application Codes in Mobile Device Cloud

Mobile Device Cloud (MDC) has become a promising collaborative cloud computing environment that exploits idle resources on nearby mobile devices to execute compute-intensive applications. In the existing MDC system, user tasks are executed by the worker devices either voluntarily or with an amount that leads to overpayment resulting dissatisfaction for both user and worker devices. Therefore, a major challenge is to minimize the execution cost of user codes while supporting sufficient payments to the workers for their used resources. Furthermore, selection of reputed workers becomes more complicated when the workers are having heterogeneous resources. In this paper, we formulate a greedy algorithm to minimize the task execution cost with reputed worker devices, while maintaining the desired quality of execution. The simulation results exhibit that our proposed algorithm can minimize the task execution cost up to 30 % compared to a state-of-the-art work.