Abstract
With mobile applications' ever-increasing demands for memory capacity, along with a steady increase in the number of applications running concurrently, memory capacity is becoming a scarce resource on mobile devices. When the memory pressure is high, current mobile OSes often kill application processes that have not been used recently to reclaim memory space. This leads to a long delay when a user relaunches the killed application, which degrades the user experience. Even if this mechanism is disabled to utilize a compression-based in-memory swap mechanism, relaunching the application still incurs a substantial latency penalty as it requires the decompression of compressed anonymous pages and a stream of I/O accesses to retrieve file-backed pages into memory. This paper identifies conventional demand paging as the primary source of this inefficiency and proposes ASAP, a mechanism for fast application switch via adaptive prepaging on mobile devices. ASAP performs prepaging by combining i) high-precision switch footprint estimators for both file-backed and anonymous pages, and ii) efficient implementation of the prepaging mechanism to minimize resource waste for CPU cycles and disk bandwidth during an application switch. Our evaluation using eight real-world applications on Google Pixel 4 and Pixel 3a demonstrates that ASAP can reduce the switch time by 22.2% and 28.3% on average, respectively (with a maximum of 33.3% and 35.7%, respectively), over the vanilla Android 10.
Original language | English |
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Title of host publication | 2021 USENIX Annual Technical Conference |
Publisher | USENIX Association |
Pages | 117-130 |
Number of pages | 14 |
ISBN (Electronic) | 9781939133236 |
Publication status | Published - 2021 |
Event | 2021 USENIX Annual Technical Conference, ATC 2021 - Virtual, Online Duration: 2021 Jul 14 → 2021 Jul 16 |
Publication series
Name | 2021 USENIX Annual Technical Conference |
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Conference
Conference | 2021 USENIX Annual Technical Conference, ATC 2021 |
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City | Virtual, Online |
Period | 21/7/14 → 21/7/16 |
Bibliographical note
Funding Information:We thank Lin Zhong for shepherding this paper. This work was supported by a research grant from Samsung Research Funding & Incubation Center of Samsung Electronics under Project Number SRFC-IT1702-52. Hongil Yoon and Jae W. Lee are the corresponding authors.
Publisher Copyright:
© 2021 USENIX Annual Technical Conference. All rights reserved.
All Science Journal Classification (ASJC) codes
- Computer Science(all)