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Energy Efficient Relay Selection and Resource Allocation in D2D-Enabled Mobile Edge Computing

机译:启用D2D移动边缘计算中的节能继电器选择和资源分配

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In order to improve resource utilization and network capacity, we propose the Device-to-Device (D2D) enabled Mobile Edge Computing (MEC) system, where multiple Smart Devices (SDs) transmit the offloading data to the MEC server with the help of wireless access point (WAP) selected from multiple WAPs. The SD uses the chosen WAP as the communication relay between the MEC server and itself. Aimed to minimize the total energy consumption of the system and satisfy the SDs demand on delay, we jointly optimize relay selection and resource allocation in D2D-enabled MEC system. The problem is formulated as an integer-mixed non-convex optimization problem which is a NP-hard problem. We thus propose a two-phase optimization algorithm that jointly optimizes relay selection policy and resource allocation strategy. In first phase, the original problem is converted into a convex optimization problem by using convex optimization techniques, and the optimal relay selection policy can be achieved by solving the relay selection problem. After obtaining the relay selection policy, the original problem is transformed into a resource allocation problem solved by leveraging the Lagrange Method in the second phase. Furthermore, the proposed algorithm is a low-complexity algorithm which is associated with the root finding method. The optimal relay selection policy and resource allocation strategy can be found in polynomial time. The extensive simulation results are provided to indicate that the D2D-enabled MEC system achieves remarkable results in energy saving. Compared with other baseline methods, our proposed algorithm can not only achieve the optimal solution with less time cost, but also improve the energy efficiency and network capacity.
机译:为了提高资源利用和网络容量,我们提出了设备到设备(D2D)的移动边缘计算(MEC)系统,其中多个智能设备(SDS)在无线的帮助下将卸载数据发送到MEC服务器从多个WAP中选择的访问点(WAP)。 SD使用所选WAP作为MEC服务器之间的通信继电器。旨在最大限度地减少系统的总能耗并满足SDS对延迟的需求,我们共同优化了D2D的MEC系统中的继电器选择和资源分配。该问题被制定为整数混合的非凸优化问题,这是NP难题。因此,我们提出了一种两相优化算法,共同优化中继选择策略和资源分配策略。在第一阶段,通过使用凸优化技术将原始问题转换为凸优化问题,并且可以通过解决中继选择问题来实现最佳中继选择策略。获取继电器选择策略后,通过利用第二阶段的拉格朗日方法来改变原始问题。此外,所提出的算法是一种低复杂性算法,它与根发现方法相关联。可以在多项式时间中找到最佳中继选择策略和资源分配策略。提供了广泛的仿真结果以指示D2D的MEC系统实现了显着的节能结果。与其他基线方法相比,我们所提出的算法不仅可以通过较少的时间成本实现最佳解决方案,而且还可以提高能源效率和网络容量。

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