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Data Structures on Event Graphs

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Abstract

We investigate the behavior of data structures when the input and operations are generated by an event graph. This model is inspired by Markov chains. We are given a fixed graph G, whose nodes are annotated with operations of the type insert, delete, and query. The algorithm responds to the requests as it encounters them during a (random or adversarial) walk in G. We study the limit behavior of such a walk and give an efficient algorithm for recognizing which structures can be generated. We also give a near-optimal algorithm for successor searching if the event graph is a cycle and the walk is adversarial. For a random walk, the algorithm becomes optimal.

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Acknowledgements

We would like to thank the anonymous referees for their thorough reading of the paper and their many helpful suggestions that have improved the presentation of this paper, as well as for pointing out [4] to us.

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Authors and Affiliations

  1. Department of Computer Science, Princeton University, Princeton, USA

    Bernard Chazelle

  2. Institut für Informatik, Freie Universität Berlin, Berlin, Germany

    Wolfgang Mulzer

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  1. Bernard Chazelle
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  2. Wolfgang Mulzer
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Correspondence to Wolfgang Mulzer.

Additional information

A preliminary version appeared as B. Chazelle and W. Mulzer, Data Structures on Event Graphs in Proc. 20th ESA, pp. 313–324, 2012.

W. Mulzer was supported in part by DFG grant MU3501/1.

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Chazelle, B., Mulzer, W. Data Structures on Event Graphs. Algorithmica 71, 1007–1020 (2015). https://doi.org/10.1007/s00453-013-9838-4

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  • DOI: https://doi.org/10.1007/s00453-013-9838-4

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