journal article·2025-11-12Open access

VSwap: A New Extension to the Swap Mechanism for Enabling Swap Memory Space Optimization

Gyupin Moon, Donghyun Kang

Applied Sciences· Volume 15· Issue 22

Abstract

The memory demand of modern applications has been rapidly increasing with the continuous growth of data volume across industrial and academic domains. As a result, computing devices (i.e., IoT devices, smartphones, and tablets) often experience memory shortages that degrade system performance and quality of service by wasting CPU cycles and energy. Thus, most operating systems rely on the swap mechanism to mitigate the memory shortage situation in advance, even if the swap memory fragmentation problem occurs over time. In this paper, we analyze the fragmentation behavior of the swap memory space within storage devices over time and demonstrate that the latency of swap operations increases significantly under aged conditions. We also propose a new extension of the traditional swap mechanism, called VSwap, that mitigates the swap memory fragmentation problem in advance by introducing two core techniques, virtual migration and address remapping. In VSwap, virtual migration gathers valid swap pages scattered across multiple clusters into contiguous regions within the swap memory space, while address remapping updates the corresponding page table entries to preserve consistency after migration. For experiments, we enable VSwap on the traditional swap mechanism (i.e., kswapd) by implementing it with simple code modifications. To confirm the effectiveness of VSwap, we performed a comprehensive evaluation based on various workloads. Our evaluation results confirm that VSwap is more useful and highly valuable than the original swap mechanism. In particular, VSwap improves the overall performance up to 48.18% by harvesting available swap memory space in advance with negligible overhead; it performs close to the ideal performance.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Data Storage Technologies · Parallel Computing and Optimization Techniques · Cloud Computing and Resource Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Computer Science and Artificial Intelligence, Dongguk University-Seoul, Seoul 04620, Republic of Korea

Funding

Korea government · Ministry of Education (MOE) and the Seoul Metropolitan Government

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