...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Internet of Things Journal, IEEE >Joint Task Offloading and Computation in Cooperative Multicarrier Relaying-Based Mobile-Edge Computing Systems
【24h】

Joint Task Offloading and Computation in Cooperative Multicarrier Relaying-Based Mobile-Edge Computing Systems

机译：基于协同多载波中继移动边缘计算系统的联合任务卸载与计算

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This article studies a mobile-edge computing (MEC) system, where an access point (AP) and a relay node serve a user terminal over multicarrier subchannels. In the MEC system, the relay can assist not only task offloading but also task computation. Aiming at minimizing total energy consumption at the user terminal and the relay, the resource allocations, such as subcarrier allocation, power allocation, task partition, and offloading time and computation time allocation, are to be optimized, subject to a given task computation delay constraint. To achieve this goal, a novel cooperative MEC protocol is designed, where multicarrier subchannels are utilized for parallel task offloading by integrating the rateless coding technique. Then, under the newly designed protocol, the resource allocation optimization problem is formulated as a mixed-integer programming (MIP) problem that is challenging to solve. To tackle this MIP problem, continuous relaxation and algebraic transformation techniques are applied to transform it into a convex problem in order to reveal the lower bound of energy consumption performance. After that, by equivalently rewriting the integer subcarrier allocation constraint in the original optimization problem as the intersection of a convex set and a d.c. (difference of two convex sets) set, the problem is solved by the successive convex approximation to achieve a practical and efficient resource allocation scheme. Simulation results show that the proposed jointly cooperative task offloading and computation scheme can significantly reduce the energy consumption as compared to the baseline schemes, where the relay only assists the task offloading or task computation.
机译：本文研究了移动边缘计算（MEC）系统，其中接入点（AP）和中继节点在多载波子信道上使用用户终端。在MEC系统中，继电器不仅可以帮助任务卸载，而且还可以帮助任务计算。旨在最小化用户终端和继电器的总能耗，资源分配，例如子载波分配，功率分配，任务分区和卸载时间和计算时间分配，受到给定的任务计算延迟约束。为了实现这一目标，设计了一种新颖的合作MEC协议，其中通过集成不多不可图的编码技术来利用多载波子信道进行并行任务卸载。然后，在新设计的协议下，资源分配优化问题被制定为混合整数编程（MIP）问题，这些问题是具有挑战性的。为了解决这个MIP问题，应用连续放松和代数变换技术以将其转换为凸面问题，以揭示能量消耗性能的下限。之后，通过等同地重写原始优化问题中的整数子载波分配约束作为凸集和D.C的交叉点。 （两个凸集的差异）设置，通过连续的凸近似来解决问题，以实现实际和高效的资源分配方案。仿真结果表明，与基线方案相比，所提出的联合合作任务卸载和计算方案可以显着降低能耗，其中继电器仅帮助任务卸载或任务计算。

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