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Skyline Algorithms on Streams of Multidimensional Data

  • Alexander Tzanakas
  • Eleftherios TiakasEmail author
  • Yannis Manolopoulos
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 637)

Abstract

We compare three algorithms for skyline processing on streams of multidimensional data with centralized processing, namely, the LookOut, Lazy and Eager methods, with different dataset types and dimensionalities, data cardinalities and sliding window sizes. Experimental results for time performance and memory consumption are presented. In addition, the problem of computing the exclusive dominance region in higher dimensions is reviewed and a novel correct solution is proposed.

Keywords

Memory Consumption Skyline Query Expiry Time Minimum Bounding Rectangle Slide Window Size 
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 International Publishing Switzerland 2016

Authors and Affiliations

  • Alexander Tzanakas
    • 1
  • Eleftherios Tiakas
    • 1
    Email author
  • Yannis Manolopoulos
    • 1
  1. 1.Department of InformaticsAristotle UniversityThessalonikiGreece

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