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International Symposium on Cyber Security Cryptography and Machine Learning

CSCML 2020: Cyber Security Cryptography and Machine Learning pp 237–244Cite as

Average-Case Competitive Ratio of Scheduling Algorithms of Multi-user Cache

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12161))

Abstract

The goal of this paper is to present an efficient realistic metric for evaluating cache scheduling algorithms in multi-user multi-cache environments. In a previous work, the requests sequence was set deliberately by an opponent (offline optimal) algorithm in an extremely unrealistic way, leading to an unlimited competitive ratio and to extremely unreasonable and unrealistic cache management strategies. In this paper, we propose to analyze the performance of cache management in a typical scenario, i.e., we consider all possibilities with their (realistic) distribution. In other words, we analyze the average case and not the worst case of scheduling scenarios. In addition, we present an efficient, according to our novel average case analysis, online heuristic algorithm for cache scheduling. The algorithm is based on machine-learning concepts, it is flexible and easy to implement.

We thank the Lynne and William Frankel Center for Computer Science, the Rita Altura Trust Chair in Computer Science. This research was also supported by a grant from the Ministry of Science & Technology, Israel & the Japan Science and Technology Agency (JST), Japan, DFG German-Israeli collaborative projects, and the Milken Families Foundation Chair in Mathematics.

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Author information

Authors and Affiliations

  1. Department of Math, Ben-Gurion University of the Negev, 84105, Beer-Sheva, Israel

    Daniel Berend

  2. Department of Computer Science, Ben-Gurion University of the Negev, 84105, Beer-Sheva, Israel

    Daniel Berend, Shlomi Dolev & Marina Kogan-Sadetsky

  3. Department of Computer Science, Bar-Ilan University, 52900, Ramat Gan, Israel

    Avinatan Hassidim

Authors
  1. Daniel Berend
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  2. Shlomi Dolev
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  3. Avinatan Hassidim
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  4. Marina Kogan-Sadetsky
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Corresponding author

Correspondence to Marina Kogan-Sadetsky .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Ben-Gurion University of the Negev, Be'er Sheva, Israel

    Shlomi Dolev

  2. School of Computer Science, Georgia Institute of Technology, Atlanta, GA, USA

    Vladimir Kolesnikov

  3. Tata Consultancy Services, Chennai, Tamil Nadu, India

    Sachin Lodha

  4. Department of Computer Science, Ben-Gurion University of the Negev, Be'er Sheva, Israel

    Gera Weiss

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Cite this paper

Berend, D., Dolev, S., Hassidim, A., Kogan-Sadetsky, M. (2020). Average-Case Competitive Ratio of Scheduling Algorithms of Multi-user Cache. In: Dolev, S., Kolesnikov, V., Lodha, S., Weiss, G. (eds) Cyber Security Cryptography and Machine Learning. CSCML 2020. Lecture Notes in Computer Science(), vol 12161. Springer, Cham. https://doi.org/10.1007/978-3-030-49785-9_15

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  • DOI: https://doi.org/10.1007/978-3-030-49785-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49784-2

  • Online ISBN: 978-3-030-49785-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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