Virtual Memory Partitioning for Enhancing Application Performance in Mobile Platforms

TL;DR

This paper introduces a novel virtual memory partitioning technique for mobile devices that isolates application memory, reducing performance degradation caused by traditional memory management methods like LMK and OOMK.

Contribution

It proposes a new OS-level virtual memory partitioning approach that improves application performance during memory shortages on mobile platforms.

Findings

Improved application execution time under memory shortage.

Reduced thrashing and fragmentation in memory management.

Enhanced user responsiveness during low-memory conditions.

Abstract

Recently, the amount of running software on smart mobile devices is gradually increasing due to the introduction of application stores. The application store is a type of digital distribution platform for application software, which is provided as a component of an operating system on a smartphone or tablet. Mobile devices have limited memory capacity and, unlike server and desktop systems, due to their mobility they do not have a memory slot that can expand the memory capacity. Low memory killer (LMK) and out-of-memory killer (OOMK) are widely used memory management solutions in mobile systems. They forcibly terminate applications when the available physical memory becomes insufficient. In addition, before the forced termination, the memory shortage incurs thrashing and fragmentation, thus slowing down application performance. Although the existing page reclamation mechanism is designed to secure available memory, it could seriously degrade user responsiveness due to the thrashing. Memory management is therefore still important especially in mobile devices with small memory capacity. This paper presents a new memory partitioning technique that resolves the deterioration of the existing application life cycle induced by LMK and OOMK. It provides a completely isolated virtual memory node at the operating system level. Evaluation results demonstrate that the proposed method improves application execution time under memory shortage, compared with methods in previous studies.