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Algorithms and Framework for Comparison of Bee-Intelligence Based Peer-to-Peer Lookup

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Advances in Swarm Intelligence (ICSI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7928))

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Abstract

Peer-to-peer has proven to be a scalable technology forretrieval of information that is widely spread among distributed sites and that is subject to dynamic changes. However, selection of a right search algorithm depends on many factors related to actual data content and application problem at hand. A comparison of different algorithms is difficult, especially if many different approaches (intelligent or unintelligent ones) shall be evaluated fairly and possibly also in combinations. In this paper, we describe a generic architectural pattern that serves as an overlay network based on autonomous agents and decentralized control. It supports plugging of different algorithms for searching and retrieving data, and thus eases comparison of algorithms in various topology configurations. A further novelty is to use bee intelligence for the lookup problem, spot optimal parameters’ settings, and evaluate the bee algorithm by using the architectural pattern to benchmark it with other algorithms.

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Author information

Authors and Affiliations

  1. Institute of Computer Languages, Technical University Vienna, Argentinierstrasse 8, 1040, Wien, Austria

    Vesna Šešum-Čavić & Eva Kühn

Authors
  1. Vesna Šešum-Čavić
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  2. Eva Kühn
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), School of lectronics Engineering and Computer Science, Department of Machine Intelligence, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 215123, Suzhou, China

    Yuhui Shi

  3. Automation College, Harbin Engineering University, 150001, Harbin, China

    Hongwei Mo

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Šešum-Čavić, V., Kühn, E. (2013). Algorithms and Framework for Comparison of Bee-Intelligence Based Peer-to-Peer Lookup. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38703-6_48

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  • DOI: https://doi.org/10.1007/978-3-642-38703-6_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38702-9

  • Online ISBN: 978-3-642-38703-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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