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QoE-Aware Task Offloading for Time Constraint Mobile Applications

机译：时间受限的移动应用程序的QoE感知任务分载

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摘要

In this paper, we develop an access controller management model which provides new opportunities for further reducing the computation repetition and data transmission redundancy for Mobile Edge Computing (MEC) in 5G network. We propose novel algorithms for solving the offloading problem with consideration of tradeoff between energy consumption and the amount of offloaded data under constraint of overall task computation time. For sequential topology applications, we develop a dynamic programming algorithm to produce optimal solutions. For general topology applications, a critical-path based heuristic algorithm is proposed by repeatedly identifying partial critical path (PCP) from the application task graph and calculating optimal solution for the PCP by performing the proposed dynamic programming algorithm. In addition, the interference of parallel data transmission between tasks (one-to-many, many-to-one and many-to-many) using single channel is taken into consideration. Experimental results demonstrate the effectiveness of our proposed method.
机译：在本文中，我们开发了一种访问控制器管理模型，该模型为进一步减少5G网络中移动边缘计算（MEC）的计算重复和数据传输冗余提供了新的机会。我们提出了一种新的算法来解决卸载问题，该算法考虑了在总任务计算时间的约束下能耗与卸载数据量之间的折衷。对于顺序拓扑应用，我们开发了一种动态编程算法来产生最佳解决方案。对于一般拓扑应用，提出了一种基于关键路径的启发式算法，方法是从应用任务图中反复标识部分关键路径（PCP），然后通过执行所提出的动态规划算法来为PCP计算最佳解决方案。另外，考虑了使用单个通道的任务（一对多，多对一和多对多）之间并行数据传输的干扰。实验结果证明了我们提出的方法的有效性。

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