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首页> 外文期刊>Future generation computer systems >Energy efficient task allocation and energy scheduling in green energy powered edge computing
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Energy efficient task allocation and energy scheduling in green energy powered edge computing

机译：绿色能源动力边缘计算中的节能任务分配和能源调度

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摘要

The ever-increasing computation tasks and communication traffic have imposed a heavy burden on cloud data centers and also resulted in a significantly high energy consumption. To ease such burden, edge computing is proposed to explore the distributed resources of edge devices (e.g., base stations) to provision the cloud services for latency-sensitive applications at the network edge. Owing to the geo-distribution of edge devices, edge computing is also an ideal energy efficient platform to leverage the distributed green energy for energy efficient computing. Thus, it is natural to integrate Energy Internet (EI) technology into edge computing for customizable energy scheduling. In such EI supported edge computing, both the green energy generation rates and the data processing demands vary in different time and space. To pursue high energy efficiency, it is desirable to maximize the utilization of green energy so as to reduce the brown energy consumption. This requires careful task allocation and energy scheduling to match the energy provision and demand. In this paper, we investigate the energy cost minimization problem with joint consideration of VM migration, task allocation and green energy scheduling and prove its NP-hardness. To tackle the computation complexity, a heuristic algorithm approximating the optimal solution is proposed. Through extensive simulations, we show that the proposed algorithm can efficiently reduce brown energy consumption and perform much close to the optimal solution. (C) 2019 Elsevier B.V. All rights reserved.
机译：不断增加的计算任务和通信流量给云数据中心带来了沉重负担，并导致了很高的能耗。为了减轻这种负担，提出了边缘计算以探索边缘设备（例如，基站）的分布式资源，以在网络边缘为延迟敏感的应用提供云服务。由于边缘设备的地理位置分布，边缘计算也是一种理想的节能平台，可利用分布式绿色能源进行节能计算。因此，自然而然地将能源互联网（EI）技术集成到边缘计算中以实现可定制的能源调度。在这种EI支持的边缘计算中，绿色能源的产生速率和数据处理需求在不同的时间和空间中都不同。为了追求高能源效率，期望最大化绿色能源的利用以减少棕色能源的消耗。这需要仔细的任务分配和能源调度以匹配能源供应和需求。在本文中，我们结合VM迁移，任务分配和绿色能源调度来研究能源成本最小化问题，并证明其NP硬度。为了解决计算复杂性，提出了一种近似最优解的启发式算法。通过广泛的仿真，我们证明了所提出的算法可以有效地减少棕色能源的消耗，并且性能与最佳解决方案非常接近。 （C）2019 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Future generation computer systems》 |2019年第6期|89-99|共11页
  • 作者

    Gu Lin; Cai Jingjing; Zeng Deze; Zhang Yu; Jin Hai; Dai Weiqi;

  • 作者单位

    Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Serv Comp Technol & Syst Lab, Big Data Technol & Syst Lab,Cluster & Grid Comp L, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Serv Comp Technol & Syst Lab, Big Data Technol & Syst Lab,Cluster & Grid Comp L, Wuhan, Hubei, Peoples R China;

    China Univ Geosci, Sch Comp Sci, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Serv Comp Technol & Syst Lab, Big Data Technol & Syst Lab,Cluster & Grid Comp L, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Serv Comp Technol & Syst Lab, Big Data Technol & Syst Lab,Cluster & Grid Comp L, Wuhan, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Serv Comp Technol & Syst Lab, Big Data Technol & Syst Lab,Cluster & Grid Comp L, Wuhan, Hubei, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Green energy; Edge computing; VM migration; Task allocation; Energy allocation; Energy efficiency;

    机译：绿色能源;边缘计算;虚拟机迁移;任务分配;能源分配;能源效率;

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