云环境下基于神经网络和群搜索优化的资源分配机制
Resource Allocation Scheme Based on Neural Network and Group Search Optimization in Cloud Environment
查看参考文献38篇
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文摘
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在云环境下,各种闲置资源可以通过池化形成资源池,进而利用虚拟化技术将资源池中的不同资源组合以服务的形式提供给用户使用,因此需要合理而有效的机制来分配资源.针对云环境下资源的特点,将经济学和智能方法相结合,提出了一种基于双向组合拍卖的智能资源分配机制.在该机制中,提出了基于体验质量(quality of experience,简称QoE)的威望系统,引入威望衰减系数和用户信誉度,降低拍卖中恶意行为造成的影响,为资源交易提供QoE支持.对拍卖中的竞价决策,综合考虑多种因素,提出了基于BP神经网络的竞标价格决策机制,不仅可以合理确定竞标价,而且使价格可以动态适应市场变化.最后,由于组合拍卖胜标确定问题是NP完全的,因此引入群搜索优化算法,以市场盈余和总体威望为优化目标,得到资源分配方案.仿真研究结果表明,该机制是可行和有效的. |
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其他语种文摘
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In cloud environment, all kinds of idle resources can be pooled to establish a resource pool, and different kinds of resources can be combined as a service to the users through virtualization. Therefore, an effective scheme is necessary for managing and allocating the resources. In this paper, economic and intelligent methods are employed to form an intelligent resource allocation scheme based on double combinatorial auction with respect to the characteristics of resources in cloud environment. In the proposed scheme, a reputation system on the basis of quality of experience (QoE) is devised, and the reputation attenuation coefficient and the user credit degree are introduced to decrease the negative effects of malicious behaviors on resource auctions, providing QoE support to resource dealing. In order to determine bidding price rationally, a bidding price decision mechanism based on back propagation (BP) neural network is presented to comprehensively consider various influence factors to make price adapt to the fluctuating market. Finally, due to the fact that the problem of winner determination in combinatorial auction is NP-complete, a group search optimization algorithm is adopted to find the specific resource allocation solution with market surplus and total reputation optimized. Simulation studies are conducted to demonstrate the feasibility and effectiveness of the proposed scheme. |
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来源
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软件学报
,2014,25(8):1858-1873 【核心库】
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DOI
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10.13328/j.cnki.jos.004555
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关键词
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云计算
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双向组合拍卖
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体验质量
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威望
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BP神经网络
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群搜索优化
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地址
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东北大学信息科学与工程学院, 中国科学院网络化控制系统重点实验室, 辽宁, 沈阳, 110819
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1000-9825 |
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学科
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自动化技术、计算机技术 |
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基金
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国家自然科学基金国家杰出青年科学基金
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国家教育部高等学校博士学科点专项科研基金
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中央高校基本科研业务费专项资金
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文献收藏号
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CSCD:5214433
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参考文献 共
38
共2页
|
|
1.
Rehr J J. Scientific computing in the cloud.
Computing in science & Engineering,2010,12(3):34-43
|
被引
2
次
|
|
|
|
|
2.
Niyato D. Economic analysis of resource market in cloud computing environment.
Proc. of the 2009 IEEE Asia-Pacific Services Computing Conf. (APSCC 2009),2009:156-162
|
被引
1
次
|
|
|
|
|
3.
Buyya R. The grid economy.
Proc. of the IEEE,2005,93(3):698-714
|
被引
26
次
|
|
|
|
|
4.
Grosu D. Auctioning resources in grids: Model and protocols.
Concurrency and Computation: Practice & Experience,2006,18(15):1909-1927
|
被引
1
次
|
|
|
|
|
5.
Tan Z. Market-Based grid resource allocation using a stable continuous double auction.
Proc. of the 8th IEEE/ACM Int'l Conf. on Grid Computing (GRID 2007),2007:283-290
|
被引
1
次
|
|
|
|
|
6.
Xia Q F. A novel grid resource scheduling model based on extended second price sealed auction.
Proc. of the 3rd Int'l Symp. on Parallel Architectures, Algorithms and Programming (PAAP 2010),2010:305-310
|
被引
1
次
|
|
|
|
|
7.
Qureshi K. Markup based continuous double auction for resource allocation in market grid.
Engineering e-Transaction,2011,6(1):50-54
|
被引
1
次
|
|
|
|
|
8.
Danak A. Efficient bidding in dynamic grid markets.
IEEE Trans. on Parallel and Distributed Systems,2011,22(9):1483-1496
|
被引
1
次
|
|
|
|
|
9.
李立. 基于组合双向拍卖的网格资源分配.
电子学报,2009,37(1):165-169
|
被引
9
次
|
|
|
|
|
10.
翁楚良. 一种基于双向拍卖机制的计算网格资源分配方法.
计算机学报,2006,29(6):1004-1009
|
被引
17
次
|
|
|
|
|
11.
李明楚. 基于非完全信息博弈的网格资源分配模型.
软件学报,2012,23(2):428-438
|
被引
5
次
|
|
|
|
|
12.
Wang X W. A reverse auction based allocation mechanism in the cloud computing environment.
Applied Mathematics & Information Sciences,2013,7(1L):75-84
|
被引
9
次
|
|
|
|
|
13.
Wang X W. A resource allocation method based on the limited English combinatorial auction under cloud computing environment.
Proc. of the 2012 9th Int'l Conf. on Fuzzy Systems and Knowledge Discovery (FSKD 2012),2012:905-909
|
被引
1
次
|
|
|
|
|
14.
Lin W Y. Dynamic auction mechanism for cloud resource allocation.
Proc. of the 10th IEEE/ACM Int'l Conf. on Cluster, Cloud, and Grid Computing (CCGrid 2010),2010:591-592
|
被引
1
次
|
|
|
|
|
15.
Prodan R. Double auction-based scheduling of scientific applications in distributed grid and cloud environments.
Journal of Grid Computing,2011,9(4):531-548
|
被引
4
次
|
|
|
|
|
16.
Shang S F. DABGPM: A double auction Bayesian game-based pricing model in cloud market.
Proc. of the IFIP Int'l Conf. on Network and Parallel Computing (NPC 2010),2010:155-164
|
被引
1
次
|
|
|
|
|
17.
Sun D W. Efficient Nash equilibrium based cloud resource allocation by using a continuous double auction.
Proc. of the 2010 Int'l Conf. on Computer Design and Applications (ICCDA 2010),2010:94-99
|
被引
1
次
|
|
|
|
|
18.
Shang S F. A knowledge-based continuous double auction model for cloud market.
Proc. of the 6th Int'l Conf. on Semantics, Knowledge and Grid (SKG 2010),2010:129-134
|
被引
1
次
|
|
|
|
|
19.
Vilajosana X. A multi-lane double auction for economic-based service management in the cloud.
Proc. of the Intelligent Networking, Collaborative Systems and Applications,2011:117-148
|
被引
1
次
|
|
|
|
|
20.
Roovers J. A reverse auction market for cloud resources.
Proc. of the 8th Int'l Workshop on Economics of Grids, Clouds, Systems, and Services (GECON 2011),2012:32-45
|
被引
1
次
|
|
|
|
|
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