Spring Buddy: A Self-Adaptive Elastic Memory Management Scheme for Efficient Concurrent Allocation/Deallocation in Cloud Computing Systems

Yihui Lu, Weidong Liu, Chentao Wu*, Jia Wang, Xiaoming Gao, Jie Li, Minyi Guo

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

2 Citations (Scopus)

Abstract

Within the cloud computing scenario, each server usually carries multiple service processes, which intensifies the concurrency pressure of the system. As a result, the process of memory management during page allocation and deallocation becomes a significant bottleneck. Although several methods such as Buddy System and Inverse Buddy System (iBuddy) have been proposed to improve the performance of memory management, they cannot adapt to the highly concurrent environment of cloud computing, because they either force the memory allocation/deallocation requests to be serialized or bring extra fragmentation. To address the above problem, we propose Spring Buddy, which improves the concurrency of both memory allocation and deallocation and avoids unnecessary fragmentation. It can detect the changes of system- and process-level memory request patterns and dynamically adjust the organization of page frames. Inventively, Spring Buddy uses the spring core layer to provide both concurrent response and resource aggregation capability which is adapted to the system's concurrency pressure, and also uses the spring lazy layer to further mitigate the system resource contention through process behavior prediction. To demonstrate the effectiveness of Spring Buddy, we implement it in the Linux kernel. The results demonstrate that Spring Buddy can reduce memory allocation latency by 71.47 % and deallocation latency by 93.20% on average compared to the existing methods.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 27th International Conference on Parallel and Distributed Systems, ICPADS 2021
PublisherIEEE Computer Society
Pages402-409
Number of pages8
ISBN (Electronic)9781665408783
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event27th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2021 - Beijing, China
Duration: 14 Dec 202116 Dec 2021

Publication series

NameProceedings of the International Conference on Parallel and Distributed Systems - ICPADS
Volume2021-December
ISSN (Print)1521-9097

Conference

Conference27th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2021
Country/TerritoryChina
CityBeijing
Period14/12/2116/12/21

Keywords

  • buddy system
  • memory allocation/deallocation
  • memory management
  • resource contention
  • scalability

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