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Application-aware cloudlet selection for computation offloading in multi-cloudlet environment

机译:面向应用程序的小云选择,用于在多小云环境中进行计算分流

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摘要

Latency- and power-aware offloading is a promising issue in the field of mobile cloud computing today. To provide latency-aware offloading, the concept of cloudlet has evolved. However, offloading an application to the most appropriate cloudlet is still a major challenge. This paper has proposed an application-aware cloudlet selection strategy for multi-cloudlet scenario. Different cloudlets are able to process different types of applications. When a request comes from a mobile device for offloading a task, the application type is verified first. According to the application type, the most suitable cloudlet is selected among multiple cloudlets present near the mobile device. By offloading computation using the proposed strategy, the energy consumption of mobile terminals can be reduced as well as latency in application execution can be decreased. Moreover, the proposed strategy can balance the load of the system by distributing the processes to be offloaded in various cloudlets. Consequently, the probability of putting all loads on a single cloudlet can be dealt for load balancing. The proposed algorithm is implemented in the mobile cloud computing laboratory of our university. In the experimental analyses, the sorting and searching processes, numerical operations, game and web service are considered as the tasks to be offloaded to the cloudlets based on the application type. The delays involved in offloading various applications to the cloudlets located at the university laboratory, using proposed algorithm are presented. The mathematical models of total power consumption and delay for the proposed strategy are also developed in this paper.
机译:时延和功耗感知卸载是当今移动云计算领域中一个有希望的问题。为了提供可感知延迟的卸载,cloudlet的概念得到了发展。但是,将应用程序卸载到最合适的cloudlet仍然是一个重大挑战。本文针对多云场景提出了一种应用感知的云选择策略。不同的小云能够处理不同类型的应用程序。当移动设备发出卸载任务的请求时,将首先验证应用程序类型。根据应用类型,在移动设备附近存在的多个小云中选择最合适的小云。通过使用所提出的策略卸载计算,可以减少移动终端的能耗,并可以减少应用程序执行中的等待时间。此外,所提出的策略可以通过将要卸载的进程分布在各个小云中来平衡系统的负载。因此,可以解决将所有负载置于单个cloudlet上的可能性以实现负载平衡。该算法在我校移动云计算实验室中实现。在实验分析中,基于应用程序类型,将排序和搜索过程,数值运算,游戏和Web服务视为要移交给cloudlets的任务。提出了使用提议的算法将各种应用程序卸载到位于大学实验室的cloudlet时所涉及的延迟。本文还为所提出的策略开发了总功耗和时延的数学模型。

著录项

  • 来源
    《Journal of supercomputing》 |2017年第4期|1672-1690|共19页
  • 作者单位

    West Bengal Univ Technol, Dept Comp Sci & Engn, BF 142,Sect 1, Kolkata 700064, W Bengal, India;

    West Bengal Univ Technol, Dept Comp Sci & Engn, BF 142,Sect 1, Kolkata 700064, W Bengal, India;

    West Bengal Univ Technol, Dept Comp Sci & Engn, BF 142,Sect 1, Kolkata 700064, W Bengal, India;

    Univ Melbourne, Cloud Comp & Distributed Syst CLOUDS Lab, Dept Comp & Informat Syst, Melbourne, Vic, Australia|Manjrasoft Pty Ltd, Melbourne, Vic, Australia;

  • 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

    Cloudlet; Offloading; AppSpecCloudlet; Power reduction; Delay reduction;

    机译:Cloudlet;卸载;AppSpecCloudlet;功耗降低;延迟降低;

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