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Joint optimization of data placement and scheduling for improving user experience in edge computing

机译:联合优化数据放置和调度以改善边缘计算中的用户体验

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摘要

In recent years, edge computing becomes an increasingly popular alternative. Edge computing allows the computation is implemented in the edge of network, in which the data are stored in the edge of network, to improve the efficiency of data process. However, some resource management techniques in cloud or distributed system cannot better suit for edge computing. Therefore, there exist some challenges on the performance improvement of edge computing. In this paper, the main purpose is to combine the optimal placement of data blocks and the optimal scheduling of tasks to reduce the computation delay and response time for the submitted tasks and improve user experience in edge computing. In optimal placement of data blocks, the value of the data blocks considers not only the popularity of the data blocks, but the data storage capacity and replacement ratios of an edge server that will store those data blocks. Furthermore, the replacement cost for placed data blocks is regarded as an important component of data block placement. This optimal placement scheme can avoid replacing the placed data blocks repeatedly so that the bandwidth overhead is reduced. In optimal scheduling of tasks, the containers are taken as the lightweight resource unit for the services for user requests to make full use of data storage in edge servers and improve the services performance of edge servers. Finally, extensive experiments are conducted to value the performance of task scheduling strategy. The results show that the performance of the proposed task scheduling algorithm is better than that of the compared algorithms. (C) 2018 Elsevier Inc. All rights reserved.
机译:近年来,边缘计算已成为一种越来越流行的替代方法。边缘计算允许在网络边缘进行计算,其中数据存储在网络边缘,以提高数据处理效率。但是,云或分布式系统中的某些资源管理技术无法更好地适合边缘计算。因此,在边缘计算的性能改进上存在一些挑战。本文的主要目的是将数据块的最佳放置和任务的最佳调度相结合,以减少提交任务的计算延迟和响应时间,并改善边缘计算的用户体验。在最佳放置数据块时,数据块的值不仅考虑数据块的普及程度,还考虑数据存储容量和将存储这些数据块的边缘服务器的替换率。此外,放置的数据块的更换成本被认为是放置数据块的重要组成部分。这种最佳的放置方案可以避免重复替换放置的数据块,从而减少了带宽开销。在优化任务调度中,将容器作为用户请求服务的轻量级资源单元,以充分利用边缘服务器中的数据存储并提高边缘服务器的服务性能。最后,进行了大量实验以评估任务调度策略的性能。结果表明,所提任务调度算法的性能优于比较算法。 (C)2018 Elsevier Inc.保留所有权利。

著录项

  • 来源
    《Journal of Parallel and Distributed Computing》 |2019年第3期|93-105|共13页
  • 作者单位

    Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430063, Hubei, Peoples R China|Tongji Univ, Key Lab Embedded Syst & Serv Comp, Minist Educ, Shanghai 201804, Peoples R China|Henan Univ Technol, Key Lab Grain Informat Proc & Control, Minist Educ, Zhengzhou 450000, Henan, Peoples R China;

    Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430063, Hubei, Peoples R China;

    Wuhan Univ Technol, Sch Comp Sci & Technol, Wuhan 430063, Hubei, Peoples R China;

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

    Data placement; Task scheduling; Edge computing; User experience;

    机译:数据放置;任务调度;边缘计算;用户体验;

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