Population Game Based Energy and Time Aware Task Offloading for Large Amounts of Competing Users
Résumé
Computation offloading is envisioned as a promising solution to resource scarcity problem on mobile devices. Mobile users can offload computation intensive tasks to remote cloud with stronger capabilities. In order to execute tasks in cloud, mobile users have to upload computational data through cellular networks. When large amounts of mobile users in the same cell attempt to offload mobile tasks through the base station, the communication latencies for data transmissions may be high due to limited bandwidth resources. However, since the task completion times are constrained by hard deadlines, this restricts the feasible set of computational tasks that can be uploaded. In this paper, we propose a population game based approach to achieve efficient computation offloading for large amounts of competing mobile users, where each user is aimed to minimize his energy consumption. This game is subject to the task execution deadlines, user specific data rates, and the competition over the shared communication channel. We analyze the evolutionary dynamic of the game and show that the game always admits a Nash equilibrium. We then design a computation offloading mechanism that can achieve a Nash equilibrium of the game. Numerical results demonstrate that the proposed mechanism can achieve efficient computation offloading performance and scale well as the system size increases.