Data Structures on Event Graphs

  • Bernard Chazelle
  • Wolfgang Mulzer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7501)


We investigate the behavior of data structures when the input and operations are generated by an event graph. This model is inspired by the model of 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 (adversarial or random) 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.


Markov Chain Hamiltonian Path Event Graph Markov Source Cancellation Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bernard Chazelle
    • 1
  • Wolfgang Mulzer
    • 2
  1. 1.Department of Computer SciencePrinceton UniversityUSA
  2. 2.Institut für InformatikFreie Universität BerlinGermany

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