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Task Execution Cost Minimization-based Joint Computation Offloading and Resource Allocation for Cellular D2D Systems

机译:任务执行成本最小化基于最小化的联合计算卸载和蜂窝D2D系统的资源分配

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In this paper, we consider a cellular device-to-device (D2D) system which consists of one base station (BS) deployed with a mobile edge computing (MEC) server, and a number of users. By defining task execution cost as the weighted sum of execution latency and energy consumption, the joint computation offloading and resource allocation problem is formulated as a task execution cost minimization problem under the constraints of task requirement, computation offloading, resource allocation and task partition, etc. As the formulated optimization problem is a mixed integer nonlinear problem, which cannot be solved conveniently, we decompose it into two subproblems, i.e., computation offloading subproblem and resource allocation subproblem, and solve the two subproblems by applying Kuhn-Munkres algorithm and Lagrange dual method, respectively. Numerical results demonstrate the effectiveness of the proposed scheme.
机译:在本文中,我们考虑一个蜂窝设备到设备(D2D)系统,该系统由部署的一个基站(BS)组成,所述基站(BS)部署为移动边缘计算(MEC)服务器以及许多用户。通过将任务执行成本定义为加权执行延迟和能量消耗,在任务要求,计算卸载,资源分配和任务分区的约束下,将联合计算卸载和资源分配问题构成为任务执行成本最小化问题。 。作为配制的优化问题是一个混合整数的非线性问题,它不能方便地解决,我们将其分解为两个子问题,即计算卸载子地图和资源分配子发布,并通过应用Kuhn-Munkres算法和拉格朗日双子来解决两个子问题方法分别。数值结果证明了提出方案的有效性。

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