Redundancy Analysis and Elimination on Access Patterns of the Windows Applications Based on I/O Log Data

Jun Ha Lee, Hyuk Yoon Kwon

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

In this paper, we analyze I/O log data monitored in the Windows operating system for improving the system performance. Especially, we focus on the I/O operations to the Windows registry. As a result, we identify redundant access patterns of the Windows applications. To find all the possible redundant patterns from the large-scale log data, we propose the redundancy detection algorithm. Then, we propose the two-level redundancy elimination method to remove unnecessary redundant operations. We also present an event-driven method that guarantees that the result of redundancy elimination is equivalent to that of the original program. Through experiments, we show that the proposed redundancy elimination method improves the performance of the original program having redundant access patterns by up to 90.25% for individual access patterns; by 8.93% 26.21% when the multiple programs having combined access patterns are running concurrently.

Original languageEnglish
Article number8950307
Pages (from-to)40640-40655
Number of pages16
JournalIEEE Access
Volume8
DOIs
StatePublished - 2020

Keywords

  • Access pattern analysis
  • I/O log data
  • Redundancy elimination
  • Windows registry

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