关注用户服务评价反馈的云资源再分配方法

doi:10.11772/j.issn.1001-9081.2015.07.1837

计算机应用 ›› 2015, Vol. 35 ›› Issue (7): 1837-1842.DOI: 10.11772/j.issn.1001-9081.2015.07.1837

关注用户服务评价反馈的云资源再分配方法

匡桂娟^1,2,3, 曾国荪^1,3, 熊焕亮^1,3,4

1. 同济大学计算机科学与技术系, 上海 200092;
2. 青岛农业大学理学与信息学院, 山东青岛 266109;
3. 国家高性能计算机工程技术中心同济分中心, 上海 200092;
4. 江西农业大学软件学院, 南昌 330045

收稿日期:2015-02-03 修回日期:2015-03-29 出版日期:2015-07-10 发布日期:2015-07-17
通讯作者: 曾国荪(1964-),男,江西吉安人,教授,博士生导师,CCF高级会员,主要研究方向:并行计算、可信网络软件、信息安全,gszeng@tongji.edu.cn
作者简介:匡桂娟(1972-),女,山东青岛人,讲师,博士研究生,CCF会员,主要研究方向:并行分布计算、云计算; 熊焕亮(1977-),男,江西新建人,讲师,博士研究生,CCF会员,主要研究方向:并行分布式计算、云计算。
基金资助:
国家863计划项目(2009AA012201);国家自然科学基金资助项目(61272107,61202173,61103068);上海市优秀学科带头人计划项目(10XD1404400);江西省自然科学基金资助项目(20151BAB207040);华为创新研究计划项目(IRP-2013-12-03);高效能服务器和存储技术国家重点实验室开放基金资助项目(2014HSSA10)。

Cloud resource re-allocation method focusing on user's evaluation feedback

KUANG Guijuan^1,2,3, ZENG Guosun^1,3, XIONG Huanliang^1,3,4

1. Department of Computer Science and Technology, Tongji University, Shanghai 200092, China;
2. School of Science and Information Science, Qingdao Agricultural University, Qingdao Shandong 266109, China;
3. Tongji Branch, National Engineering and Technology Center of High Performance Computer, Shanghai 200092, China;
4. Software College, Jiangxi Agricultural University, Nanchang Jiangxi 330045, China

Received:2015-02-03 Revised:2015-03-29 Online:2015-07-10 Published:2015-07-17

摘要/Abstract

摘要：

针对以往关于云资源管理分配的研究中多从云运营商的角度出发,未充分利用用户评价来改善资源决策能力的问题,提出了一种关注用户服务评价反馈的资源再分配方法。首先,通过分析云中心资源分配的过程,抽取出影响资源决策的要素,提出关注用户服务评价的自适应云资源分配框架;其次,阐明用户服务评价参与云资源管理的基本原理,建议一种用户服务满意度的量化度量;最后,基于相似性理论,预测用户对新任务的期望满意度,合并用户任务参数以及当前环境参数,作为BP神经网络的输入,进行资源分配方案的决策。在和无用户评价参与的资源分配方案比较的仿真实验中,其平均用户满意度提高了7.4%,保持在0.8以上,总体呈稳定上升趋势;与Min-Max算法、云任务与云资源满意婚配(CTRSM)算法比较,平均用户满意度分别提高了16.7%和4.6%。实验结果表明关注用户服务评价反馈的资源再分配方法是能够自我完善的,能够提高云资源自适应管理的能力。

关键词: 云计算, 资源再分配, 用户评价, 自适应, 神经网络

Abstract:

Concerning the problem that previous studies mostly consider from the resource provider's perspective, and user's evaluations have not been fully utilized to improve the resource decision making ability, this paper proposed a resource re-allocation method focusing on the user's evaluation feedback. First, through analyzing the process of cloud resource allocation, several factors influencing decision-making were defined, and an adaptive cloud resource management framework with user's involvement was proposed. Next, the main idea of method of resource re-allocation with user's involvement was elaborated, and a formula was designed to guide user's evaluation. Finally, based on similarity theory, the user's expected satisfaction of a new cloud task was predicted. Together with the cloud task parameters and environment parameters, it was used to be the input of BP (Back Propagation) neural network to make the resource allocation decision. In the comparison experiments with the allocation scheme without user's involvement, the average user's satisfactory of the proposed scheme increased by 7.4%, maintained at more than 0.8, showed a steady upward trend. In the comparison experiments with Min-Max algorithm and Cloud Tasks-Resources Satisfactory Matching (CTRSM) algorithm, its average user's satisfactory increased by 16.7% and 4.6% respectively. The theoretical analysis and simulation results show that the cloud resource re-allocation method focusing on user's evaluation is self-improved, and it can improve the adaptive ability of cloud resource management.

Key words: cloud computing, resource re-allocation, user evaluation, self-adaptive, neural network

中图分类号:

TP338
TP391

匡桂娟, 曾国荪, 熊焕亮. 关注用户服务评价反馈的云资源再分配方法[J]. 计算机应用, 2015, 35(7): 1837-1842.

KUANG Guijuan, ZENG Guosun, XIONG Huanliang. Cloud resource re-allocation method focusing on user's evaluation feedback[J]. Journal of Computer Applications, 2015, 35(7): 1837-1842.

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关注用户服务评价反馈的云资源再分配方法

Cloud resource re-allocation method focusing on user's evaluation feedback

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