Nothing Special   »   [go: up one dir, main page]

skip to main content
short-paper

Miss behavior for caching with lease

Published: 16 September 2015 Publication History

Abstract

Caching with lease is to evict the data record from cache after its associated lease term expires. This policy differs from the traditional caching algorithms, e.g., LRU, by introducing a dimension of time to the data record stored in the cache. This model has recently attracted increasing interest not only from a theoretical perspective, but also in real system implementation. For the related theoretical studies, lease of each data record, also known as cache characteristic time and Time-To-Live (TTL), provides a convenient approximation that can simplify the complexity in analyzing popular caching algorithms such as LRU. This approach ignores the finite capacity of the cache size and assumes the lease term to be a known parameter that matches with the measurements. Recently, with new development in system engineering, caching with lease has been shown to be an efficient way to improve the performance of RDMA based key-value stores. This engineering practice imposes new challenges for designing caching algorithms based on lease. It calls for further theoretical investigation on the lease term in presence of a finite cache capacity. To this end, we derive the miss probabilities for caching with lease compared to LRU, when the frequency of requesting a data record is equal to the generalized Zipf's law. Based on the miss probability depending on the lease term, we also discuss adaptive algorithms that can optimally determine the lease term.

References

[1]
Memcached. http://memcached.org/.
[2]
Redis. http://redis.io/.
[3]
O. Bahat and A. M. Makowski. Measuring consistency in ttl-based caches. Performance Evaluation, 62(1- 4):439--455, October 2005.
[4]
D. S. Berger, P. Gland, S. Singla, and F. Ciucu. Exact analysis of ttl cache networks. pages 2--23, Turin, Italy, October 2014.
[5]
H. Che, Y. Tung, and Z. Wang. Hierarchical Web caching systems: modeling, design and experimental results. Selected Areas in Communications, IEEE Journal on, 20(7):1305--1314, September 2002.
[6]
N. E. Choungmo Fofack, D. Towsley,M. Badov,M. Dehghan, and D. L. Goeckel. An approximate analysis of heterogeneous and general cache networks. INRIA Research Report RR-8516, April 2014.
[7]
E. Cohen, E. Halperin, and H. Kaplan. Performance aspects of distributed caches using, ttl-based consistency. Theoretical Computer Science, 331(1):73--96, February 2005.
[8]
A. Dan and D. Towsley. An approximate analysis of the lru and fifo buffer replacement schemes. In Proceedings of the 1990 ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, SIGMETRICS '90, pages 143--152, University of Colorado, Boulder, Colorado, USA, 1990. ACM.
[9]
B. Fan, D. G. Andersen, and M. Kaminsky. Memc3: Compact and concurrent memcache with dumber caching and smarter hashing. In Proceedings of the 10th USENIX Conference on Networked Systems Design and Implementation, NSDI'13, pages 371--384, Lombard, IL, 2013. USENIX Association.
[10]
J. Fill. An exact formula for the move-to-front rule for self-organizing lists. Journal of Theoretical Probability, 9(1):113--160, 1996.
[11]
P. Flajolet, D. Gardy, and L. Thimonier. Birthday paradox, coupon collectors, caching algorithms and self-organizing search. Discrete Applied Mathematics, 39(3):207--229, November 1992.
[12]
N. Fofack, P. Nain, G. Neglia, and D. Towsley. Analysis of ttl-based cache networks. In Performance Evaluation Methodologies and Tools (VALUETOOLS), 6th International Conference on, pages 1--10, October 2012.
[13]
Y. T. Hou, J. Pan, B. L. 0001, and S. S. Panwar. On expiration-based hierarchical caching systems. IEEE Journal on Selected Areas in Communications, 22(1):134--150, 2004.
[14]
P. R. Jelenković. Asymptotic approximation of the move-to-front search cost distribution and leastrecently- used caching fault probabilities. The Annals of Applied Probability, (2):430--464, 1999.
[15]
P. R. Jelenković and A. Radovanović. Least-recentlyused caching with dependent requests. Theoretical Computer Science, 326(1-3):293--327, Oct. 2004.
[16]
V. Martina, M. Garetto, and E. Leonardi. A unified approach to the performance analysis of caching systems. In Proceedings of IEEE INFOCOM, Toronto, Canada, 2014.
[17]
E. J. Rosensweig, J. Kurose, and D. Towsley. Approximate models for general cache networks. In Proceedings of the 29th Conference on Information Communications, INFOCOM'10, pages 1100--1108, San Diego, California, USA, 2010. IEEE Press.
[18]
Y. Wang, X. Meng, L. Zhang, and J. Tan. C-hint: An effective and reliable cache management for rdmaaccelerated key-value stores. In Proceedings of the ACM Symposium on Cloud Computing, SOCC '14, pages 23:1--23:13, Seattle, WA, USA, 2014. ACM.

Cited By

View all
  • (2018)On Resource Pooling and Separation for LRU CachingProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/31794082:1(1-31)Online publication date: 3-Apr-2018

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM SIGMETRICS Performance Evaluation Review
ACM SIGMETRICS Performance Evaluation Review  Volume 43, Issue 2
September 2015
79 pages
ISSN:0163-5999
DOI:10.1145/2825236
Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 September 2015
Published in SIGMETRICS Volume 43, Issue 2

Check for updates

Qualifiers

  • Short-paper

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 12 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2018)On Resource Pooling and Separation for LRU CachingProceedings of the ACM on Measurement and Analysis of Computing Systems10.1145/31794082:1(1-31)Online publication date: 3-Apr-2018

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media