基于最佳匹配拍卖的企业级网络资源分配策略

丛鑫; 訾玲玲; 沈学利

doi:10.11959/j.issn.1000-436x.2019186

您当前的位置：

首页 >

文章列表页 >

基于最佳匹配拍卖的企业级网络资源分配策略

学术通信 | 更新时间：2024-06-05

- 基于最佳匹配拍卖的企业级网络资源分配策略
- Resource allocation strategy based on optimal matching auction in the enterprise network
- 通信学报 2019年40卷第8期页码：212-222
- 作者机构：
  
  辽宁工程技术大学电子与信息工程学院，辽宁葫芦岛125105
- 作者简介：
  
  [ "丛鑫（1982- ），男，辽宁阜新人，博士，辽宁工程技术大学高级工程师、硕士生导师，主要研究方向为P2P技术、云计算、流媒体和虚拟网络映射。" ]
  [ "訾玲玲（1981- ），女，辽宁阜新人，博士，辽宁工程技术大学副教授、硕士生导师，主要研究方向为图形图像与多媒体。" ]
  [ "沈学利（1969- ），男，江苏连云港人，辽宁工程技术大学教授、硕士生导师，主要研究方向为网络及信息安全。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61602227);国家自然科学基金资助项目(61702241);辽宁省教育厅科学研究一般项目(LJYL019);辽宁省科技厅博士启动基金计划资助项目(201601365)
- DOI：10.11959/j.issn.1000-436x.2019186
  中图分类号： TP393
- 网络出版日期：2019-08，
  
  纸质出版日期：2019-08-25
- 稿件说明：
移动端阅览
丛鑫, 訾玲玲, 沈学利. 基于最佳匹配拍卖的企业级网络资源分配策略[J]. 通信学报, 2019,40(8):212-222.

Xin CONG, Lingling ZI, Xueli SHEN. Resource allocation strategy based on optimal matching auction in the enterprise network[J]. Journal on communications, 2019, 40(8): 212-222.
丛鑫, 訾玲玲, 沈学利. 基于最佳匹配拍卖的企业级网络资源分配策略[J]. 通信学报, 2019,40(8):212-222. DOI： 10.11959/j.issn.1000-436x.2019186.

Xin CONG, Lingling ZI, Xueli SHEN. Resource allocation strategy based on optimal matching auction in the enterprise network[J]. Journal on communications, 2019, 40(8): 212-222. DOI： 10.11959/j.issn.1000-436x.2019186.

摘要

针对企业级网络中计算机拥有者的自私属性导致网络中可用资源节点数量不足和资源分配效率低的问题，提出一种以拍卖机制为核心的企业级网络最优匹配资源分配（OMRA）策略，在抑制节点自私性的同时提升网络可用资源数，进而提升整个拍卖市场的运行效率。首先，归一化不同类型资源的成本，确定拍卖初始的资源请求价格；其次，设计了最优化匹配的拍卖算法，最大化拍卖市场的收益；再次，运行服务请求预取算法，使资源提供者能以当前的成交价格获取更多的任务请求，保证资源提供者的收益；最后，利用请求价格和竞拍价格更新算法，保证买卖双方在下一轮拍卖过程中获得较高的优先级，以获取更多的收益。实验结果表明，与基于拍卖的云资源分配算法（CRAA/FA）相比，所提OMRA策略能提升10%的资源分配效率和11.4%的市场收益率。

Abstract

To address the issue that the owners of computer are selfish in the enterprise networks

which caused the low available number of resource nodes and low efficiency of resource allocation

an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA

so as the operating efficiency of the whole auction market was improved.First

the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly

an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then

service perfecting algorithm was performed such that the sellers could get more services at the current transaction value

thus ensuring the benefits of resource providers.At last

a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA)

the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.

关键词

Keywords

references

KENT A D , LIEBROCK L M , NEIL J C . Authentication graphs:analyzing user behavior within an enterprise network [J ] . Computers ＆Security , 2015 , 48 ( 7 ): 150 - 166 .

DOMEIJ R , LUONG R . Estimation of resource allocation based on disturbance prediction data with use of statistics,machine learning and data analysis [D ] . Lund:Lund University , 2017 :E19.

SINGH S , CHANA I , BUYYA R . STAR:SLA-aware autonomic management of cloud resources [J ] . IEEE Transactions on Cloud Computing , 2017 ,PP( 99 ):1.

YAO Y , CAO J , JIANG Y S . A pattern prediction-based elastic workflow service in the cloud [C ] // IEEE International Conference on Web Services . IEEE , 2017 : 784 - 791 .

SHIRVASTAVA S , DUBEY R , SHRIVASTAVA M . Best fit based VM allocation for cloud resource allocation [J ] . International Journal of Computer Applications , 2017 , 158 ( 9 ): 25 - 27 .

PRASAD G V , PRASAD A S , RAO S . A combinatorial auction mechanism for multiple resource procurement in cloud computing [J ] . IEEE Transactions on Cloud Computing , 2018 , 6 ( 4 ): 904 - 914 .

MARUFU A M C , KAYEM A V D M , WOLTHUSEN S D . Circumventing cheating on power auctioning in resource constrained micro-grids [C ] // 2016 IEEE 18th International Conference on High Performance Computing and Communications . IEEE , 2016 : 137 - 149 .

FAN Q , ZEITOUNI K , XIONG N , et al . Nash equilibrium-based semantic cache in mobile sensor grid database systems [J ] . IEEE Transactions on Systems Man ＆ Cybernetics Systems , 2017 , 47 ( 9 ): 2550 - 2561 .

SUN D , CHANG G , WANG C , et al . Efficient Nash equilibrium based cloud resource allocation by using a continuous double auction [C ] // International Conference on Computer Design ＆ Applications . IEEE , 2010 : 94 - 99 .

FARAJIAN N , ZAMANIFAR K . Intelligent continuous double auction method for service allocation in cloud computing [J ] . Brain Broad Research in Artificial Intelligence ＆ Neuroscience , 2017 ( 10 ): 74 - 83 .

CONG X , SHUANG K , SU S , et al . LBAS:an effective pricing mechanism towards video migration in cloud-assisted VoD system [J ] . Computer Networks , 2014 , 64 ( 8 ): 15 - 25 .

ZHANG H , JIANG D , LI F , et al . Cluster-based resource allocation for spectrum-sharing femtocell networks [J ] . IEEE Access , 2017 , 4 ( 99 ): 8643 - 8656 .

肖丁 , 贾亚璞 , 石川 . 云计算环境下的非线性能耗建模方法 [J ] . 北京邮电大学学报 , 2016 , 39 ( 1 ): 107 - 111 .

XIAO D , JIA Y P , SHI C . Non-liner energy consumption model for cloud computing [J ] . Journal of Beijing University of Posts and Telecommunications , 2016 , 39 ( 1 ): 107 - 111 .

GUENTER B , JAIN N , WILLIAMS C . Managing cost,performance,and reliability tradeoffs for energy-aware server provisioning [C ] // International Conference on Computer Communications (INFOCOM) . IEEE , 2011 : 1332 - 1340 .

ANTHONY P , JENNINGS N R . Developing a bidding agent for multiple heterogeneous auctions [J ] . ACM Transactions on Internet Technology , 2003 , 2 ( 3 ): 185 - 217 .

WANG H B , KANG Z , WANG L . Performance-aware cloud resource allocation via fitness-enabled auction [J ] . IEEE Transactions on Parallel and Distributed Systems , 2016 , 27 ( 4 ): 1160 - 1173 .

浏览量

585

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于耦合相移STAR-RIS的认知无线电系统资源分配算法

基于深度确定性策略梯度的星地融合网络可拆分任务卸载算法

基于图卷积神经网络的超密集物联网资源分配策略

低地球轨道卫星边缘计算场景中任务卸载与资源分配联合优化算法

基于终端流量预测的低地球轨道卫星互联网资源分配策略