• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Physical Communication >Joint task scheduling and uplink/downlink radio resource allocation in PD-NOMA based mobile edge computing networks
【24h】

Joint task scheduling and uplink/downlink radio resource allocation in PD-NOMA based mobile edge computing networks

机译：基于PD-NOMA的移动边缘计算网络中的联合任务调度和上行/下行无线资源分配

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Mobile edge computing (MEC) is a new paradigm that brings the computation capabilities closer to the edge of wireless networks. In doing so, the computation tasks of users can be offloaded to the network edge for remote executing. Since both the computing and transmission delays in uplink and downlink of each task offloading operation affect the total task execution delays, it is necessary to utilize the physical layer transmission opportunities in the task allocation algorithms. In this regard, we develop an efficient algorithm to minimize the total execution delay of users in a single-cell power-domain non-orthogonal multiple access (PD-NOMA) based MEC system with multiple users and single MEC server. Hence the computation task of each user can be partitioned into two separated parts, one for offloading to the network edge and another for locally computing. In the considered partial offloading scheme, we jointly obtain subcarrier and transmit power allocation policies for both the uplink and downlink transmissions with task scheduling and computation resource allocation at both the users and the MEC server. Numerical results demonstrate that when the communication and computation resources are jointly optimized at the task allocation algorithms, the network performance is improved nearly 30% compared to the existing joint computation and task allocation approach in which both the downlink and uplink data rates are assumed to be fixed. (C) 2018 Elsevier B.V. All rights reserved.
机译：移动边缘计算（MEC）是一种新的范例，它使计算功能更接近无线网络的边缘。这样，可以将用户的计算任务卸载到网络边缘以进行远程执行。由于每个任务卸载操作的上行链路和下行链路中的计算和传输延迟都影响总任务执行延迟，因此有必要在任务分配算法中利用物理层传输机会。在这方面，我们开发了一种有效的算法，以在具有多个用户和单个MEC服务器的基于单小区功率域非正交多路访问（PD-NOMA）的MEC系统中最大程度地减少用户的总执行延迟。因此，每个用户的计算任务可以分为两个独立的部分，一个用于卸载到网络边缘，另一个用于本地计算。在考虑的部分卸载方案中，我们通过用户和MEC服务器上的任务调度和计算资源分配，共同获得上行链路和下行链路传输的子载波和传输功率分配策略。数值结果表明，与现有的联合计算和任务分配方法（假定下行链路和上行链路数据速率均被认为是）相比，当使用任务分配算法共同优化通信和计算资源时，网络性能提高了近30％。固定。 （C）2018 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号