Resource allocation strategy based on optimal matching auction in the enterprise network

Xin CONG; Lingling ZI; Xueli SHEN

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

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Resource allocation strategy based on optimal matching auction in the enterprise network

Correspondences | 更新时间：2024-06-05

- Resource allocation strategy based on optimal matching auction in the enterprise network
- Journal on Communications Vol. 40, Issue 8, Pages: 212-222(2019)
- 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：
- 基金信息：
  
  The National Natural Science Foundation of China(61602227);The National Natural Science Foundation of China(61702241);The Foundation of Liaoning Educational Committee(LJYL019);The Doctoral Starting up Foundation of Science Project of Liaoning Province(201601365)
- DOI：10.11959/j.issn.1000-436x.2019186
  CLC： TP393
- Online First：2019-08，
  
  Published：25 August 2019
- 稿件说明：
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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：

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%.

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references

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