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Online computation and competitive analysisMay 1998
  • Authors:
  • Allan Borodin,
  • Ran El-Yaniv
Publisher:
  • Cambridge University Press
  • 40 W. 20 St. New York, NY
  • United States
ISBN:978-0-521-56392-5
Published:01 May 1998
Pages:
414
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Abstract

No abstract available.

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  737. Becchetti L, Leonardi S and Muthukrishnan S Scheduling to minimize average stretch without migration Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms, (548-557)
  738. Young N K-medians, facility location, and the Chernoff-Wald bound Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms, (86-95)
  739. Koutsoupias E Weak Adversaries for the k-Server Problem Proceedings of the 40th Annual Symposium on Foundations of Computer Science
  740. Goel A and Indyk P Stochastic Load Balancing and Related Problems Proceedings of the 40th Annual Symposium on Foundations of Computer Science
  741. ACM
    Cohen E, Kaplan H and Zwick U Connection caching Proceedings of the thirty-first annual ACM symposium on Theory of Computing, (612-621)
  742. ACM
    Chen G, Kao M, Lyuu Y and Wong H Optimal buy-and-hold strategies for financial markets with bounded daily returns Proceedings of the thirty-first annual ACM symposium on Theory of Computing, (119-128)
  743. Riedel M Online matching for scheduling problems Proceedings of the 16th annual conference on Theoretical aspects of computer science, (571-580)
  744. Epstein L, Noga J, Seiden S, Sgall J and Woeginger G Randomized online scheduling on two uniform machines Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms, (317-326)
  745. Plonski P, Vander Hook J, Peng C, Noori N and Isler V Navigation around an unknown obstacle for autonomous surface vehicles using a forward-facing sonar 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), (1-7)
  746. Chuprikov P, Nikolenko S and Kogan K On demand elastic capacity planning for service auto-scaling IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, (1-9)
  747. Zhao S, Lin X, Aliprantis D, Villegas H and Chen M Online multi-stage decisions for robust power-grid operations under high renewable uncertainty IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, (1-9)
  748. Zheng Z and Shroff N Online multi-resource allocation for deadline sensitive jobs with partial values in the cloud IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, (1-9)
  749. Mlika Z, Driouch E and Ajib W Deadline Scheduling in Energy Harvesting Networks: Competitive and Learning Algorithms 2019 IEEE Global Communications Conference (GLOBECOM), (1-6)
Contributors
  • University of Toronto
  • Technion - Israel Institute of Technology

Recommendations

Ralph Walter Wilkerson

The normal methods of analysis of online algorithms usually employ the techniques of average-case analysis, making assumptions about the distribution of the inputs. In competitive analysis, we compare the performance of the online algorithm to that of an optimal offline algorithm, which would have full knowledge of future inputs. Consequently, competitive analysis is much like worst-case analysis. This book presents a detailed introduction to the methods of competitive analysis. It contains numerous examples, such as list accessing, network routing, k-server systems, load balancing, search, decision theory, and game-theoretic applications. This well-written book will be of interest to students and researchers in algorithms and operations research.

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