Hybrid LRU Algorithm for Enterprise Data Hub
A. Murugan1, S. Ganesan2
1S. Ganesan*, Research Scholar, PG & Research Department of Computer Science, Dr. Ambedkar Govt Arts College, University of Madras, Chennai, India.
2A. Murugan, Associate Professor & Head, PG & Research department of Computer Science, Dr. Ambedkar Govt Arts College, University of Madras, Chennai, India.
Manuscript received on October 14, 2019. | Revised Manuscript received on 21 October, 2019. | Manuscript published on November 10, 2019. | PP: 1277-1281 | Volume-9 Issue-1, November 2019. | Retrieval Number: L34891081219/2019©BEIESP | DOI: 10.35940/ijitee.L3489.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the computing theory, cache is key concept to process the in memory data from slow storage layer into faster. Key objective is to speed up the end user requests from cache storage. As cache is limited in size, it is essential to build the efficient algorithm to replace the existing unused content from faster memory. Enterprise Data Hub makes a single golden storage to produce any kind of reports at any point of time from the various sources of any system. Data integrity and governance parameters add the credibility to this centralized data. In general, Big Data processing uses the disk based technique to handles the business logic processing. This research paper is to leverage the in memory processing for the business use case of Enterprise Data Hub. This paper provides an algorithm to handle Enterprise Data Hub in efficient design using prioritized Least Recently Used algorithm. This paper depicts about the experimental advantage of execution time optimization and efficient page/cache hit ratio, using hybrid Least Recently Used algorithm with priority mechanism. It helps the industry Enterprise Data Hub for the faster execution model.
Keywords: Prioritization, Least Recently Used, Big Data, Enterprise Data Hub, Cache Algorithm, Hybrid LRU, Cache Hit Ratio, etc.
Scope of the Article: Algorithm Engineering