4.7 Article

A Stochastic Control Approach to Maximize Profit on Service Provisioning for Mobile Cloudlet Platforms

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2016.2606400

Keywords

Dynamic scheduling; Lyapunov optimization; mobile cloud computing; queue stability; stochastic control

Funding

  1. Fundamental Research Funds for the Central Universities of China [2015JBM040, 2014JBZ003]
  2. National Natural Science Foundation of China [61202430, 61303245]
  3. State Key Laboratory of Astronautical Dynamics of China [2016ADL-DW0402]

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The recent emergence of mobile cloud computing has enabled mobile users to offload computing tasks from mobile devices to nearby cloudlets, so as to reduce energy consumption and improve application performance. In this paper, we consider the problem of maximizing the profit of the cloudlets' managing platform that receives computing requests from mobile users and fulfils these requests by leveraging computing service of participating cloudlets. However, it is very challenging to maximize the operating profit for such a managing platform, due to unpredictable arrival of user requests, dynamic participation of mobile cloudlets, and complexity in computing resource allocations. Based on the Lyapunov optimization technique combined with the technique of weight perturbation, we introduce a new stochastic control algorithm that makes online decisions on computing request admission and dispatching, computing service purchasing, and computing resource allocation. Different from traditional techniques, this algorithm does not require any statistical knowledge of relevant system dynamics, and is efficient for implementation in practice. Theoretical analysis and simulation results have demonstrated both the profit optimality and the system stability achieved by the proposed control algorithm.

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