Acclaim: Adaptive Memory Reclaim to Improve User Experience in Android Systems


Yu Liang and Jinheng Li, City University of Hong Kong; Rachata Ausavarungnirun, King Mongkut's University of Technology North Bangkok; Riwei Pan, City University of Hong Kong; Liang Shi, East China Normal University; Tei-Wei Kuo, City University of Hong Kong and National Taiwan University; Chun Jason Xue, City University of Hong Kong


While the Linux memory reclaim scheme is designed to deliver high throughput in server workloads, the scheme becomes inefficient on mobile device workloads. Through carefully designed experiments, this paper shows that the current memory reclaim scheme cannot deliver its desired performance due to two key reasons: page re-fault, which occurs when an evicted page is demanded again soon after, and direct reclaim, which occurs when the system needs to free up pages upon request time. Unlike the server workload where the direct reclaim happens infrequently, multiple direct reclaims can happen in many common Android use cases. We provide further analysis that identifies the major sources of the high number of page re-faults and direct reclaims and propose Acclaim, a foreground aware and size-sensitive reclaim scheme. Acclaim consists of two parts: foreground aware eviction (FAE) and lightweight prediction-based reclaim scheme (LWP). FAE is used to relocate free pages from background applications to foreground applications. While LWP dynamically tunes the size and the amount of background reclaims according to the predicted allocation workloads. Experimental results show Acclaim can significantly reduce the number of page re-faults and direct reclaims with low overheads and delivers better user experiences for mobile devices.

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@inproceedings {254404,
author = {Yu Liang and Jinheng Li and Rachata Ausavarungnirun and Riwei Pan and Liang Shi and Tei-Wei Kuo and Chun Jason Xue},
title = {Acclaim: Adaptive Memory Reclaim to Improve User Experience in Android Systems},
booktitle = {2020 USENIX Annual Technical Conference (USENIX ATC 20)},
year = {2020},
isbn = {978-1-939133-14-4},
pages = {897--910},
url = {},
publisher = {USENIX Association},
month = jul

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