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A lazy buddy system bounded by two coalescing delays

Published: 01 November 1989 Publication History

Abstract

The watermark-based lazy buddy system for dynamic memory management uses lazy coalescing rules controlled by watermark parameters to achieve low operational costs. The correctness of the watermark-based lazy buddy system is shown by defining a space of legal states called the lazy space and proving that the watermark-based lazy coalescing rules always keep the memory state within that space. In this paper we describe a different lazy coalescing policy, called the DELAY-2 algorithm, that focuses directly on keeping the memory state within the lazy space. The resulting implementation is simpler, and experimental data shows it to be up to 12% faster than the watermark-based buddy system and about 33% faster than the standard buddy system. Inexpensive operations make the DELAY-2 algorithm attractive as a memory manager for an operating system.
The watermark-based lazy buddy policy offers fine control over the coalescing policy of the buddy system. However, applications such as the UNIX System kernel memory manager do not need such fine control. For these applications, the DELAY-2 buddy system provides an efficient memory manager with low operational costs and low request blocking probability. In the DELAY-2 buddy system, the worst-case time for a free operation is bounded by two coalescing delays per class, and when all blocks are returned to the system, the system memory is coalesced back to its original state. This ensures that the memory space can be completely shared.

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T. P. Lee and R. E. B arkley, "A Watermark-based Lazy Buddy System for Kernel Memory Allocation," Proc. of the 1989 Summer USENiX Conference, June 1989, pp. 1-13.
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  • (2024)MLDPBS: A Machine Learning based Dynamic Partitioning Buddy System for Efficient Memory Allocation in Embedded Systems2024 IEEE 17th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)10.1109/MCSoC64144.2024.00051(261-268)Online publication date: 16-Dec-2024
  • (2015)iBuddy: Inverse Buddy for Enhancing Memory Allocation/Deallocation Performanceon Multi-Core SystemsIEEE Transactions on Computers10.1109/TC.2013.229604964:3(720-732)Online publication date: 1-Mar-2015
  • (2013)A Novel Defragmemtable Memory Allocating Schema for MMU-Less Embedded SystemAdvances in Intelligent Systems and Applications - Volume 210.1007/978-3-642-35473-1_74(751-757)Online publication date: 2013
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Published In

cover image ACM Conferences
SOSP '89: Proceedings of the twelfth ACM symposium on Operating systems principles
November 1989
224 pages
ISBN:0897913388
DOI:10.1145/74850
  • cover image ACM SIGOPS Operating Systems Review
    ACM SIGOPS Operating Systems Review  Volume 23, Issue 5
    Dec. 3–6, 1989
    223 pages
    DOI:10.1145/74851
    • Editor:
    • Roy Levin
    Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 November 1989

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Cited By

View all
  • (2024)MLDPBS: A Machine Learning based Dynamic Partitioning Buddy System for Efficient Memory Allocation in Embedded Systems2024 IEEE 17th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)10.1109/MCSoC64144.2024.00051(261-268)Online publication date: 16-Dec-2024
  • (2015)iBuddy: Inverse Buddy for Enhancing Memory Allocation/Deallocation Performanceon Multi-Core SystemsIEEE Transactions on Computers10.1109/TC.2013.229604964:3(720-732)Online publication date: 1-Mar-2015
  • (2013)A Novel Defragmemtable Memory Allocating Schema for MMU-Less Embedded SystemAdvances in Intelligent Systems and Applications - Volume 210.1007/978-3-642-35473-1_74(751-757)Online publication date: 2013
  • (2011)Automatic Memory Management for Embedded Real-Time Java Processor Jpor-32Intelligent Automation & Soft Computing10.1080/10798587.2011.1064322117:8(1193-1205)Online publication date: Jan-2011
  • (2010)Online memory compression for embedded systemsACM Transactions on Embedded Computing Systems10.1145/1698772.16987859:3(1-30)Online publication date: 5-Mar-2010
  • (2009)IGCEJProceedings of the 2009 First IEEE International Conference on Information Science and Engineering10.1109/ICISE.2009.645(248-252)Online publication date: 26-Dec-2009
  • (2006)A Low Energy Key Management Scheme in Wireless Sensor Networks2006 First International Conference on Communications and Networking in China10.1109/CHINACOM.2006.344894(1-5)Online publication date: Oct-2006
  • (2006)Fast and Efficient Memory Management for Non-FIFO Routers2006 First International Conference on Communications and Networking in China10.1109/CHINACOM.2006.344693(1-8)Online publication date: Oct-2006
  • (1999)A high-performance hardware-efficient memory allocation technique and designProceedings 1999 IEEE International Conference on Computer Design: VLSI in Computers and Processors (Cat. No.99CB37040)10.1109/ICCD.1999.808436(274-276)Online publication date: 1999
  • (1996)A high performance memory allocator for object-oriented systemsIEEE Transactions on Computers10.1109/12.48557445:3(357-366)Online publication date: Mar-1996
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