Affiliations: [a] School of Economics and Management, Huainan Normal University, Huainan, China
| [b] NYU, Courant Institute of Mathematical Sciences, New York, NY, USA
Correspondence:
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Corresponding author. Guoqiang Wu, School of Economics and Management, Huainan Normal University, Huainan 232038, China. E-mail: [email protected].
Abstract: The current resource integration algorithm lacks the consideration of users’ needs, which can cause high violation of service-level agreement and poor data quality after integration. It affects the energy consumption and service quality of data center. To address this problem, a financial resource integration algorithm of virtual enterprise based on improved artificial bee colony in big data environment is proposed in this paper. The improved PageRank algorithm is used to extract the financial resource of virtual enterprise. The extracted resource is transformed. From the unified data resource centralization after transformation, service resources that satisfy users’ needs and constraints are selected and combined. An improved artificial bee colony algorithm is applied to dynamically integrate service resources for different needs. Experimental results show that the proposed algorithm can effectively reduce the energy consumption of the data center, improve the data quality and user service satisfaction. The advantages and feasibility of the proposed algorithm in the integration of virtual enterprise financial resources under the big data environment are verified.
Keywords: Big data environment, virtual resource, enterprise financial resource, resource integration, PageRank algorithm
