An Optimization Scheme for Bank Batch Processing Based on Cloud Computation

Abstract:

Most commercial banks have put their business and data processing into centralized IT&Data centers. Fast business developments require IT centers to handle increasing number and volumes of batch processing; new challenges are how to make full use of available IT resources and have flexible configurations. Cloud Computation is changing the manner how information system architecture is to be redesigned to meet higher service level and IT cost constraints. The core features of IT resource and application virtualization in cloud computation could increase IT center performance and optimize resource allocation algorithms for batch processing in banking, e_commerce and other tense and large-scaled data processing industries. A batch processing optimization scheme is presented which consists in creating a dynamic model by dividing business process into parallel and independent tasks to whom are allocated adequate IT resources. An experimental environment based on Hadoop/MapReduce framework is set up to simulate the performance of the proposed scheme, the simulation results show inspiring advantages which encourage further research and application work.

• Periodical: Applied Mechanics and Materials (Volume 539)
• Pages: 339-344
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.539.339
• Online since: July 2014
• Authors: Xi Zhao*, Guang Ming Li
• Keywords: Batch Processing, Cloud Computation, Resource Allocation

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