{"title":"FragPicker","authors":"Jonggyu Park, Young Ik Eom","doi":"10.1145/3477132.3483593","DOIUrl":null,"url":null,"abstract":"File fragmentation has been widely studied for several decades because it negatively influences various I/O activities. To eliminate fragmentation, most defragmentation tools migrate the entire content of files into a new area. Unfortunately, such methods inevitably generate a large amount of I/Os in the process of data migration. For this reason, the conventional tools (i) cause defragmentation to be time-consuming, (ii) significantly degrade the performance of co-running applications, and (iii) even curtail the lifetime of modern storage devices. Consequently, the current usage of defragmentation is very limited although it is necessary. Our extensive experiments discover that, unlike HDDs, the performance degradation of modern storage devices incurred by fragmentation mainly stems from request splitting, where a single I/O request is split into multiple ones. With this insight, we propose a new defragmentation tool, FragPicker, to minimize the amount of I/Os induced by defragmentation, while significantly improving I/O performance. FragPicker analyzes the I/O activities of applications and migrates only those pieces of data that are crucial to the I/O performance, in order to mitigate the aforementioned problems of existing tools. Experimental results demonstrate that FragPicker efficiently reduces the amount of I/Os for defragmentation while achieving a similar level of performance improvement to the conventional defragmentation schemes.","PeriodicalId":38935,"journal":{"name":"Operating Systems Review (ACM)","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operating Systems Review (ACM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3477132.3483593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 1
Abstract
File fragmentation has been widely studied for several decades because it negatively influences various I/O activities. To eliminate fragmentation, most defragmentation tools migrate the entire content of files into a new area. Unfortunately, such methods inevitably generate a large amount of I/Os in the process of data migration. For this reason, the conventional tools (i) cause defragmentation to be time-consuming, (ii) significantly degrade the performance of co-running applications, and (iii) even curtail the lifetime of modern storage devices. Consequently, the current usage of defragmentation is very limited although it is necessary. Our extensive experiments discover that, unlike HDDs, the performance degradation of modern storage devices incurred by fragmentation mainly stems from request splitting, where a single I/O request is split into multiple ones. With this insight, we propose a new defragmentation tool, FragPicker, to minimize the amount of I/Os induced by defragmentation, while significantly improving I/O performance. FragPicker analyzes the I/O activities of applications and migrates only those pieces of data that are crucial to the I/O performance, in order to mitigate the aforementioned problems of existing tools. Experimental results demonstrate that FragPicker efficiently reduces the amount of I/Os for defragmentation while achieving a similar level of performance improvement to the conventional defragmentation schemes.
期刊介绍:
Operating Systems Review (OSR) is a publication of the ACM Special Interest Group on Operating Systems (SIGOPS), whose scope of interest includes: computer operating systems and architecture for multiprogramming, multiprocessing, and time sharing; resource management; evaluation and simulation; reliability, integrity, and security of data; communications among computing processors; and computer system modeling and analysis.