{"title":"Analysis of Synchronization Mechanisms in Operating Systems","authors":"Oluwatoyin Kode, Temitope Oyemade","doi":"arxiv-2409.11271","DOIUrl":null,"url":null,"abstract":"This research analyzed the performance and consistency of four\nsynchronization mechanisms-reentrant locks, semaphores, synchronized methods,\nand synchronized blocks-across three operating systems: macOS, Windows, and\nLinux. Synchronization ensures that concurrent processes or threads access\nshared resources safely, and efficient synchronization is vital for maintaining\nsystem performance and reliability. The study aimed to identify the\nsynchronization mechanism that balances efficiency, measured by execution time,\nand consistency, assessed by variance and standard deviation, across platforms.\nThe initial hypothesis proposed that mutex-based mechanisms, specifically\nsynchronized methods and blocks, would be the most efficient due to their\nsimplicity. However, empirical results showed that reentrant locks had the\nlowest average execution time (14.67ms), making them the most efficient\nmechanism, but with the highest variability (standard deviation of 1.15). In\ncontrast, synchronized methods, blocks, and semaphores exhibited higher average\nexecution times (16.33ms for methods and 16.67ms for blocks) but with greater\nconsistency (variance of 0.33). The findings indicated that while reentrant\nlocks were faster, they were more platform-dependent, whereas mutex-based\nmechanisms provided more predictable performance across all operating systems.\nThe use of virtual machines for Windows and Linux was a limitation, potentially\naffecting the results. Future research should include native testing and\nexplore additional synchronization mechanisms and higher concurrency levels.\nThese insights help developers and system designers optimize synchronization\nstrategies for either performance or stability, depending on the application's\nrequirements.","PeriodicalId":501333,"journal":{"name":"arXiv - CS - Operating Systems","volume":"191 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Operating Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.11271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This research analyzed the performance and consistency of four
synchronization mechanisms-reentrant locks, semaphores, synchronized methods,
and synchronized blocks-across three operating systems: macOS, Windows, and
Linux. Synchronization ensures that concurrent processes or threads access
shared resources safely, and efficient synchronization is vital for maintaining
system performance and reliability. The study aimed to identify the
synchronization mechanism that balances efficiency, measured by execution time,
and consistency, assessed by variance and standard deviation, across platforms.
The initial hypothesis proposed that mutex-based mechanisms, specifically
synchronized methods and blocks, would be the most efficient due to their
simplicity. However, empirical results showed that reentrant locks had the
lowest average execution time (14.67ms), making them the most efficient
mechanism, but with the highest variability (standard deviation of 1.15). In
contrast, synchronized methods, blocks, and semaphores exhibited higher average
execution times (16.33ms for methods and 16.67ms for blocks) but with greater
consistency (variance of 0.33). The findings indicated that while reentrant
locks were faster, they were more platform-dependent, whereas mutex-based
mechanisms provided more predictable performance across all operating systems.
The use of virtual machines for Windows and Linux was a limitation, potentially
affecting the results. Future research should include native testing and
explore additional synchronization mechanisms and higher concurrency levels.
These insights help developers and system designers optimize synchronization
strategies for either performance or stability, depending on the application's
requirements.