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首页> 外文期刊>IEEE communications letters >Energy-Saving Computation Offloading by Joint Data Compression and Resource Allocation for Mobile-Edge Computing
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Energy-Saving Computation Offloading by Joint Data Compression and Resource Allocation for Mobile-Edge Computing

机译:通过联合数据压缩和资源分配实现移动边缘计算的节能计算分流

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摘要

In this letter, we consider a multiuser mobile-edge computing (MEC) system with latency constraint. In order to meet the latency requirement and save energy consumption, each user can partially offload the task to the MEC server for edge computing. Data compression is applied to compress the offloaded data before transmission to reduce the data size. The problem of jointly optimizing computation offloading, data compression and resource allocation to minimize energy consumption under the latency constraint and finite MEC computation capacity is considered. We transform the non-convex problem into a convex one and apply convex optimization to solve it. The simulation results demonstrate that our proposed scheme significantly outperforms the benchmark schemes.
机译:在这封信中,我们考虑了具有延迟约束的多用户移动边缘计算(MEC)系统。为了满足延迟要求并节省能耗,每个用户可以将任务部分转移到MEC服务器上进行边缘计算。数据压缩用于在传输之前压缩卸载的数据,以减小数据大小。考虑了在延迟约束和有限的MEC计算能力下共同优化计算分流,数据压缩和资源分配以最小化能耗的问题。我们将非凸问题转化为凸问题,并应用凸优化来解决。仿真结果表明,我们提出的方案明显优于基准方案。

著录项

  • 来源
    《IEEE communications letters》 |2019年第4期|704-707|共4页
  • 作者

    Xu Ding; Li Qun; Zhu Hongbo;

  • 作者单位

    Nanjing Univ Posts & Telecommun, Wireless Commun Key Lab Jiangsu Prov, Nanjing 210003, Jiangsu, Peoples R China;

    Nanjing Univ Posts & Telecommun, Wireless Commun Key Lab Jiangsu Prov, Nanjing 210003, Jiangsu, Peoples R China;

    Nanjing Univ Posts & Telecommun, Wireless Commun Key Lab Jiangsu Prov, Nanjing 210003, Jiangsu, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Mobile-edge computing; energy efficient; task offloading; data compression;

    机译:移动边缘计算;节能;任务卸载;数据压缩;

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