An index based task assignment policy for achieving optimal power delay tradeoff in edge cloud systems
Edge cloud is a promising architecture in order to address the latency problem in mobile cloud computing. However, as compared with remote clouds, edge clouds have limited computational resources, and higher operating costs. In this paper, we design policies which carry out the assignment of tasks that are generated at the mobile subscribers with edge clouds in an online fashion. The proposed policies achieve an optimal power delay trade off in the system. Here, the delay experienced by a mobile computing task includes the time spent waiting for transmission to the edge cloud, and the execution time at the edge cloud servers. We perform a theoretical analysis after modeling the system as a continuous time queueing system. The contribution of this paper is two fold: Firstly, the algorithm to determine the optimal policy is obtained by proposing an equivalent discrete time Markov decision process. Secondly, an easily implementable index policy is proposed by analyzing the dual of the original problem. Extensive simulations illustrate the effectiveness of the proposed policies.
2016 IEEE International Conference on Communications (ICC)