Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Generalization of LRU Cache Replacement Policy with Applications to Video Streaming

Published: 20 August 2019 Publication History

Abstract

Caching plays a crucial role in networking systems to reduce the load on the network and is commonly employed by content delivery networks (CDNs) to improve performance. One of the commonly used mechanisms, Least Recently Used (LRU), works well for identical file sizes. However, for asymmetric file sizes, the performance deteriorates. This article proposes an adaptation to the LRU strategy, called gLRU, where the file is sub-divided into equal-sized chunks. In this strategy, a chunk of the newly requested file is added in the cache, and a chunk of the least-recently-used file is removed from the cache. Even though approximate analysis for the hit rate has been studied for LRU, the analysis does not extend to gLRU, since the metric of interest is no longer the hit rate as the cache has partial files. This article provides a novel approximation analysis for this policy where the cache may have partial file contents. The approximation approach is validated by simulations. Further, gLRU outperforms the LRU strategy for a Zipf file popularity distribution and censored Pareto file size distribution for the file download times. Video streaming applications can further use the partial cache contents to help the stall duration significantly, and the numerical results indicate significant improvements (32%) in stall duration using the gLRU strategy as compared to the LRU strategy. Furthermore, the gLRU replacement policy compares favorably to two other cache replacement policies when simulated on MSR Cambridge Traces obtained from the SNIA IOTTA repository.

References

[1]
V. Aggarwal, Y. F. R. Chen, T. Lan, and Y. Xiang. 2017. Sprout: A functional caching approach to minimize service latency in erasure-coded storage. IEEE/ACM Trans. Netw. 25, 6 (Dec. 2017), 3683--3694.
[2]
Oleg Ivanovich Aven, Edward Grady Coffman, and Yakov Afroimovich Kogan. 1987. Stochastic Analysis of Computer Storage, vol. 38. Springer Science 8 Business Media.
[3]
Daniel S. Berger, Ramesh K. Sitaraman, and Mor Harchol-Balter. 2017. AdaptSize: Orchestrating the hot object memory cache in a content delivery network. In Proceedings of the USENIX Symposium on Networked Systems Design and Implementation (NSDI’17). 483--498.
[4]
Lee Breslau, Pei Cao, Li Fan, Graham Phillips, and Scott Shenker. 1999. Web caching and Zipf-like distributions: Evidence and implications. In Proceedings of the 18th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM’99), vol. 1. IEEE, 126--134.
[5]
Hao Che, Ye Tung, and Zhijun Wang. 2002. Hierarchical web caching systems: Modeling, design and experimental results. IEEE J. Select. Areas Commun. 20, 7 (2002), 1305--1314.
[6]
Junesang Choi and H. M. Srivastava. 2011. Some summation formulas involving harmonic numbers and generalized harmonic numbers. Math. Comput. Model. 54, 9-10 (2011), 2220--2234.
[7]
Asaf Cidon, Assaf Eisenman, Mohammad Alizadeh, and Sachin Katti. 2016. Cliffhanger: Scaling performance cliffs in web memory caches. In Proceedings of the 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI’16). USENIX Association, Santa Clara, CA, 379--392. Retrieved from https://www.usenix.org/conference/nsdi16/technical-sessions/presentation/cidon.
[8]
Asit Dan and Don Towsley. 1990. An Approximate Analysis of the LRU and FIFO Buffer Replacement Schemes, vol. 18. ACM.
[9]
Stefan Dernbach, Nina Taft, Jim Kurose, Udi Weinsberg, Christophe Diot, and Azin Ashkan. 2016. Cache content-selection policies for streaming video services. In Proceedings of the 35th Annual IEEE International Conference on Computer Communications (INFOCOM’16). IEEE, 1--9.
[10]
Anis Elgabli and Vaneet Aggarwal. 2019. Fastscan: Robust low-complexity rate adaptation algorithm for video streaming over http. IEEE Trans. Circ. Syst. Video Technol. (2019).
[11]
A. Elgabli, V. Aggarwal, S. Hao, F. Qian, and S. Sen. 2018. LBP: Robust rate adaptation algorithm for SVC video streaming. IEEE/ACM Trans. Netw. 26, 4 (Aug. 2018), 1633--1645.
[12]
Ronald Fagin. 1977. Asymptotic miss ratios over independent references. J. Comput. Syst. Sci. 14, 2 (1977), 222--250.
[13]
Philippe Flajolet, Loÿs Thimonier, and Danièle Gardy. 1987. Birthday paradox, coupon collectors, caching algorithms and self-organizing search. Ph.D. Dissertation. INRIA.
[14]
Christine Fricker, Philippe Robert, and James Roberts. 2012a. A versatile and accurate approximation for LRU cache performance. In Proceedings of the 24th International Teletraffic Congress. International Teletraffic Congress, 8.
[15]
Christine Fricker, Philippe Robert, James Roberts, and Nada Sbihi. 2012b. Impact of traffic mix on caching performance in a content-centric network. In Proceedings of the IEEE Conference on Computer Communications Workshops (INFOCOM’12). IEEE, 310--315.
[16]
Massimo Gallo, Bruno Kauffmann, Luca Muscariello, Alain Simonian, and Christian Tanguy. 2014. Performance evaluation of the random replacement policy for networks of caches. Perform. Eval. 72 (2014), 16--36.
[17]
Michele Garetto, Emilio Leonardi, and Valentina Martina. 2016. A unified approach to the performance analysis of caching systems. ACM Trans. Model. Perform. Eval. Comput. Syst. 1, 3 (2016), 12.
[18]
Nicolas Gast and Benny Van Houdt. 2015. Transient and steady-state regime of a family of list-based cache replacement algorithms. ACM SIGMETRICS Perform. Eval. Rev. 43, 1 (2015), 123--136.
[19]
Nicolas Gast and Benny Van Houdt. 2016. Asymptotically exact ttl-approximations of the cache replacement algorithms lru (m) and h-lru. In Proceedings of the 28th International Teletraffic Congress (ITC’16), Vol. 1. IEEE, 157--165.
[20]
Sangtae Ha, Injong Rhee, and Lisong Xu. 2008. CUBIC: A new TCP-friendly high-speed TCP variant. ACM SIGOPS Operat. Syst. Rev. 42, 5 (2008), 64--74.
[21]
Janey C. Hoe. 1996. Improving the start-up behavior of a congestion control scheme for TCP. In ACM SIGCOMM Computer Communication Review, vol. 26. ACM, 270--280.
[22]
Predrag R. Jelenković and Xiaozhu Kang. 2008. Characterizing the miss sequence of the LRU cache. ACM SIGMETRICS Perform. Eval. Rev. 36, 2 (2008), 119--121.
[23]
Predrag R. Jelenković and Ana Radovanović. 2004. Optimizing LRU caching for variable document sizes. Combinator. Probabil. Comput. 13, 4--5 (2004), 627--643.
[24]
Shudong Jin and Azer Bestavros. 2000. Popularity-aware greedy dual-size web proxy caching algorithms. In Proceedings of the 20th IEEE International Conference on Distributed Computing Systems. IEEE, 254--261.
[25]
W. C. King. 1972. Analysis of paging algorithms. In Proceedings of the International Federation for Information Processing 1971 Congress, Ljubljana. North-Holland, 485--490.
[26]
Ke Liu, Zhongbin Zha, Wenkai Wan, Vaneet Aggarwal, Binzhang Fu, and Mingyu Chen. 2019. Optimizing TCP loss recovery performance over mobile data networks. IEEE Trans. Mobile Comput. (2019).
[27]
Yao Liu, Sujit Dey, Fatih Ulupinar, Michael Luby, and Yinian Mao. 2015. Deriving and validating user experience model for DASH video streaming. IEEE Trans. Broadcast. 61, 4 (2015), 651--665.
[28]
Zhengye Liu, Yanming Shen, Keith W. Ross, Shivendra S. Panwar, and Yao Wang. 2008. Substream trading: Towards an open P2P live streaming system. In Proceedings of the IEEE International Conference on Network Protocols (ICNP’08). IEEE, 94--103.
[29]
Anirban Mahanti, Carey Williamson, and Derek Eager. 2000. Traffic analysis of a web proxy caching hierarchy. IEEE Netw. 14, 3 (2000), 16--23.
[30]
Ben Manes. 2018. A ConcurrentLinkedHashMap for Java. Retrieved from https://github.com/ben-manes/concurrentlinkedhashmap.
[31]
Kianoosh Mokhtarian and Hans-Arno Jacobsen. 2014. Caching in video CDNs: Building strong lines of defense. In Proceedings of the 9th European Conference on Computer Systems. ACM, 13.
[32]
Christopher Müller and Christian Timmerer. 2011. A test-bed for the dynamic adaptive streaming over HTTP featuring session mobility. In Proceedings of the 2nd Annual ACM Conference on Multimedia Systems. ACM, 271--276.
[33]
Dushyanth Narayanan, Austin Donnelly, and Antony Rowstron. 2008. Write off-loading: Practical power management for enterprise storage. ACM Trans. Storage 4, 3 (2008), 10.
[34]
Giovanni Neglia, Damiano Carra, Mingdong Feng, Vaishnav Janardhan, Pietro Michiardi, and Dimitra Tsigkari. 2017. Access-time-aware cache algorithms. ACM Trans. Model. Perform. Eval. Comput. Syst. 2, 4 (2017), 21.
[35]
Vaidyanathan Ramaswami, Kaustubh Jain, Rittwik Jana, and Vaneet Aggarwal. 2014. Modeling heavy tails in traffic sources for network performance evaluation. In Computational Intelligence, Cyber Security, and Computational Models. Springer, 23--44.
[36]
E. J. Rosensweig and J. Kurose. 2013. A network calculus for cache networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM’13). 85--89.
[37]
Elisha J. Rosensweig, Jim Kurose, and Don Towsley. 2010. Approximate models for general cache networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM’10). IEEE, 1--9.
[38]
Giuseppe Rossini, Dario Rossi, Michele Garetto, and Emilio Leonardi. 2014. Multi-terabyte and multi-gbps information centric routers. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM’14). IEEE, 181--189.
[39]
Yago Sánchez de la Fuente, Thomas Schierl, Cornelius Hellge, Thomas Wiegand, Dohy Hong, Danny De Vleeschauwer, Werner Van Leekwijck, and Yannick Le Louédec. 2011. iDASH: Improved dynamic adaptive streaming over HTTP using scalable video coding. In Proceedings of the 2nd Annual ACM Conference on Multimedia Systems. ACM, 257--264.
[40]
Károly Simon, Sándor Molnár, Julia Komjathy, and Péter Móra. 2017. Large deviation multifractal analysis of a process modeling TCP CUBIC. arXiv preprint arXiv:1705.11039 (2017).
[41]
David Starobinski and David Tse. 2001. Probabilistic methods for web caching. Perform. Eval. 46, 2--3 (2001), 125--137.
[42]
Manik Surtani and Jason Greene. 2014. Concurrent linked hashed maps. U.S. Patent 8,719,307.
[43]
Kun-Lung Wu, Philip S. Yu, and Joel L. Wolf. 2001. Segment-based proxy caching of multimedia streams. In Proceedings of the 10th International Conference on World Wide Web. ACM, 36--44.
[44]
Junbiao Zhang, Rauf Izmailov, Daniel Reininger, and Maximilian Ott. 1999. Web caching framework: Analytical models and beyond. In Proceedings of the IEEE Workshop on Internet Applications. IEEE, 132--141.

Cited By

View all
  • (2024)Optimal Edge Caching for Individualized Demand DynamicsIEEE/ACM Transactions on Networking10.1109/TNET.2024.336961132:4(2826-2841)Online publication date: Aug-2024
  • (2024)Tackling Cold Start in Serverless Computing with Multi-Level Container Reuse2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS57955.2024.00017(89-99)Online publication date: 27-May-2024
  • (2024)Incremental Least-Recently-Used Algorithm: Good, Robust, and Predictable Performance2024 IEEE International Conference on Communications Workshops (ICC Workshops)10.1109/ICCWorkshops59551.2024.10615665(514-519)Online publication date: 9-Jun-2024
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Modeling and Performance Evaluation of Computing Systems
ACM Transactions on Modeling and Performance Evaluation of Computing Systems  Volume 4, Issue 3
September 2019
151 pages
ISSN:2376-3639
EISSN:2376-3647
DOI:10.1145/3343140
  • Editors:
  • Sem Borst,
  • Carey Williamson
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 the author(s) 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].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 August 2019
Accepted: 01 June 2019
Revised: 01 June 2019
Received: 01 June 2018
Published in TOMPECS Volume 4, Issue 3

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Caching
  2. Che’s approximation
  3. characteristic time approximation
  4. least recently used
  5. video streaming

Qualifiers

  • Research-article
  • Research
  • Refereed

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)30
  • Downloads (Last 6 weeks)2
Reflects downloads up to 10 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2024)Optimal Edge Caching for Individualized Demand DynamicsIEEE/ACM Transactions on Networking10.1109/TNET.2024.336961132:4(2826-2841)Online publication date: Aug-2024
  • (2024)Tackling Cold Start in Serverless Computing with Multi-Level Container Reuse2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS57955.2024.00017(89-99)Online publication date: 27-May-2024
  • (2024)Incremental Least-Recently-Used Algorithm: Good, Robust, and Predictable Performance2024 IEEE International Conference on Communications Workshops (ICC Workshops)10.1109/ICCWorkshops59551.2024.10615665(514-519)Online publication date: 9-Jun-2024
  • (2023)A Time Pattern-Based Intelligent Cache Optimization Policy on Korea Advanced Research NetworkIntelligent Automation & Soft Computing10.32604/iasc.2023.03644036:3(3743-3759)Online publication date: 2023
  • (2023)An Enhanced Short Video Caching Strategy Based on User Behaviour and Time Factors2023 4th International Conference on Information Science and Education (ICISE-IE)10.1109/ICISE-IE60962.2023.10456467(70-75)Online publication date: 15-Dec-2023
  • (2023)The Future of Next Generation Web: Juxtaposing Machine Learning and Deep Learning-Based Web Cache Replacement Models in Web Caching SystemsNetworks and Systems in Cybernetics10.1007/978-3-031-35317-8_39(426-450)Online publication date: 15-Jul-2023
  • (2022)Learning-Based Online QoE Optimization in Multi-Agent Video StreamingAlgorithms10.3390/a1507022715:7(227)Online publication date: 28-Jun-2022
  • (2022)Effective data management strategy and RDD weight cache replacement strategy in SparkComputer Communications10.1016/j.comcom.2022.07.008194(66-85)Online publication date: Oct-2022
  • (2020)TTLCache: Taming Latency in Erasure-Coded Storage Through TTL CachingIEEE Transactions on Network and Service Management10.1109/TNSM.2020.299817517:3(1582-1596)Online publication date: Sep-2020
  • (2019)DeepChunk: Deep Q-Learning for Chunk-Based Caching in Wireless Data Processing NetworksIEEE Transactions on Cognitive Communications and Networking10.1109/TCCN.2019.29475505:4(1034-1045)Online publication date: Dec-2019

View Options

Get Access

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media