Energy-efficient scheduling policy for collaborative execution in mobile cloud computing

In this paper, we investigate the scheduling policy for collaborative execution in mobile cloud computing. A mobile application is represented by a sequence of fine-grained tasks formulating a linear topology, and each of them is executed either on the mobile device or offloaded onto the cloud side for execution. The design objective is to minimize the energy consumed by the mobile device, while meeting a time deadline. We formulate this minimum-energy task scheduling problem as a constrained shortest path problem on a directed acyclic graph, and adapt the canonical “LARAC” algorithm to solving this problem approximately. Numerical simulation suggests that a one-climb offloading policy is energy efficient for the Markovian stochastic channel, in which at most one migration from mobile device to the cloud is taken place for the collaborative task execution. Moreover, compared to standalone mobile execution and cloud execution, the optimal collaborative execution strategy can significantly save the energy consumed on the mobile device.