Processing Capacity and Response Time Enhancement by Using Iterative Learning Approach with an Application to Insurance Policy Server Operation

  • Tankut Acarman Galatasaray University
  • Mutlu Ercan AvivaSA Retirement and Life Insurance Company

Abstract

In this study, computing system performance enhancement by using iterative learning technique is presented. Computational response time and throughput of the computing system is improved by introducing computational cost model and selection probability for each individual job. Excepted gain by enforcing dynamic caching is maximized in terms of classifying the arriving computing jobs on an selective manner and dynamically replacing them in a limited memory space. Gain maximization is performed by tuning the window size which helps to compare the computing jobs in terms of their individual selection and occurence probabilities. Fairly special computing work in insurance risk investigation is chosen for experimental validation of the proposed approach. Aspect Oriented Programming (AOP) methodology on Java platform is used for the experimental setup. AOP allows to identify computational jobs and their parameters based on the marked annotations. Experimental results show that the developed iterative learning based caching algorithm performs better than the other well known caching techniques. The design and development of iterative learning based dynamic caching minimizes the necessity of developers' decision about job results to be cached in the memory.

Author Biographies

Tankut Acarman, Galatasaray University
Dr. Acarman received his Ph.D. degree from The Ohio State University, USA in 2002 and then he joined Galatasaray University, computer engineering department where he is currently an associate professor.
Mutlu Ercan, AvivaSA Retirement and Life Insurance Company
Mr. Ercan received his M.Sc. degree in Galatasaray University in 2011.  He has been working in AvivaSA Retirement and Life Insurance Company as a developer.

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Published
2013-07-26
How to Cite
ACARMAN, Tankut; ERCAN, Mutlu. Processing Capacity and Response Time Enhancement by Using Iterative Learning Approach with an Application to Insurance Policy Server Operation. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 8, n. 4, p. 514-524, july 2013. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/8>. Date accessed: 10 aug. 2020. doi: https://doi.org/10.15837/ijccc.2013.4.8.

Keywords

iterative learning; caching; computational cost model