{"title":"Rectifying Skewed Kernel Page Reclamation in Mobile Devices for Improving User-Perceivable Latency","authors":"Yi-Quan Chou, Lin-Wei Shen, Li-Pin Chang","doi":"10.1145/3607937","DOIUrl":null,"url":null,"abstract":"A crucial design factor for users of smart mobile devices is the latency of graphical interface interaction. Switching a background app to foreground is a frequent operation on mobile devices and the latency of this process is highly perceivable to users. Based on an Android smartphone, through analysis of memory reference generated during the app-switching process, we observe that file (virtual) pages and anonymous pages are both heavily involved. However, to our surprise, the amounts of the two types of pages in the main memory are highly imbalanced, and frequent I/O operations on file pages noticeably slows down the app-switching process. In this study, we advocate to improve the app-switching latency by rectifying the skewed kernel page reclaiming. Our approach involves two parts: proactive identification of unused anonymous pages and adaptive balance between file pages and anonymous pages. As mobile apps are found inflating their anonymous pages, we propose identifying unused anonymous pages in sync with the app-switching events. In addition, Android devices replaces the swap device with RAM-based zram, and swapping on zram is much faster than file accessing on flash storage. Without causing thrashing, we propose swapping out as many anonymous pages to zram as possible for caching more file pages. We conduct experiments on a Google Pixel phone with realistic user workloads, and results confirm that our method is adaptive to different memory requirements and greatly improves the app-switching latency by up to 43% compared with the original kernel.","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Embedded Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3607937","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
A crucial design factor for users of smart mobile devices is the latency of graphical interface interaction. Switching a background app to foreground is a frequent operation on mobile devices and the latency of this process is highly perceivable to users. Based on an Android smartphone, through analysis of memory reference generated during the app-switching process, we observe that file (virtual) pages and anonymous pages are both heavily involved. However, to our surprise, the amounts of the two types of pages in the main memory are highly imbalanced, and frequent I/O operations on file pages noticeably slows down the app-switching process. In this study, we advocate to improve the app-switching latency by rectifying the skewed kernel page reclaiming. Our approach involves two parts: proactive identification of unused anonymous pages and adaptive balance between file pages and anonymous pages. As mobile apps are found inflating their anonymous pages, we propose identifying unused anonymous pages in sync with the app-switching events. In addition, Android devices replaces the swap device with RAM-based zram, and swapping on zram is much faster than file accessing on flash storage. Without causing thrashing, we propose swapping out as many anonymous pages to zram as possible for caching more file pages. We conduct experiments on a Google Pixel phone with realistic user workloads, and results confirm that our method is adaptive to different memory requirements and greatly improves the app-switching latency by up to 43% compared with the original kernel.
期刊介绍:
The design of embedded computing systems, both the software and hardware, increasingly relies on sophisticated algorithms, analytical models, and methodologies. ACM Transactions on Embedded Computing Systems (TECS) aims to present the leading work relating to the analysis, design, behavior, and experience with embedded computing systems.