移动Ad Hoc云中任务卸载的联合优化策略

Joint Optimization Strategy for Task Offloading in Mobile Ad Hoc Cloud

了降低移动AdHoc云中客户端卸载计算密集型任务过程中产生的计算能耗、传输能耗和任务时延,该文提出了一种联合优化算法。该算法首先基于计算能耗、通信能耗及任务时延进行建模;然后进行预估计,以选择更优的代理终端,并由此降低总的系统能耗与任务时延。仿真结果表明,相对于传统云算法,该算法在系统能耗和任务时延两方面均有显著提升。

In order to reduce the computational energy consumption, transmission energy consumption and task delay generated in the process of computing-intensive tasks offloaded by the clients in mobile Ad Hoc cloud, a joint optimization algorithm is proposed in this paper. Firstly, the algorithm model is established based on the computational energy consumption, communication energy consumption and task delay. Then, the algorithm is pre-estimated to select a better proxy terminal, thereby reducing the total system energy consumption and task delay. The simulation results show that compared with the traditional cloud computing algorithm, the proposed algorithm has significant improvement in both system energy consumption and task delay.