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A Design Framework for Ultra-Large-Scale Autonomic Systems

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Applications of Evolutionary Computation (EvoApplications 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6624))

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Abstract

The origins of ultra-large-scale (ULS) systems derive from social problems that are getting more and more complex, such as climatic monitoring, transportation, citizens protection and security. These factors imply a continuous increase of information systems that evolve towards ultra-dimension systems, requiring digital communication networks that allow for communication between people, between objects, and objects and people.

The aim of this paper is to present novel approaches for the engineering of highly adaptive ULS systems, with the focus on computer-supported evolution, adaptable structure, emergent behaviors as well as advanced monitoring and control techniques. We illustrate the Networked Autonomic Machine (NAM), a framework for the characterization of the elements of self-*, highly dynamic ULS systems. Moreover, we recall the Adaptive Evolutionary Framework (AEF), for the implementation of distributed evolutionary strategies. Finally, we describe an example scenario of large peer-to-peer network under targeted attacks, showing the benefits of the NAM-AEF design.

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Author information

Authors and Affiliations

  1. Distributed Systems Group, Università degli Studi di Parma, Via Usberti, 181a, Parma, Italy

    Michele Amoretti

Authors
  1. Michele Amoretti
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. Department of Computer Engineering, University of Parma, Viale Usberti 181/a, 43100, Parma, Italy

    Stefano Cagnoni

  3. Departamento de Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  4. Wilhelm-Schickard-Institut für Informatik, Universität Tübingen, Sand 1, 72076, Tübingen, Germany

    Marc Ebner

  5. Knowledge Engineering Research Group, Aston University, Aston Triangle, B4 7ET, Birmingham, UK

    Anikó Ekárt

  6. Instituto Tecnológico de Informática, Universidad Politécnica de Valencia, Edif. 8G Acceso B, 46022, Valencia, Spain

    Anna I. Esparcia-Alcázar

  7. Departamento de Electrónica y Tecnología de los Computadores, Universidad de Granada, 18071, Grenada, Spain

    Juan J. Merelo

  8. Department of Mathematical Information Technology, University of Jyväskylä, 4th Floor, P.O. Box 25, 40014, Agora, Finland

    Ferrante Neri

  9. Lehrstuhl für Algorithm Engineering, Technische Universität Dortmund, Otto-Hahn-Straße 14, 44227, Dortmund, Germany

    Mike Preuss

  10. Fakultät Elektrotechnik und Informationstechnik, HTWK Leipzig, Postfach 30 11 66, 04251, Leipzig, Germany

    Hendrik Richter

  11. Center for Computer Games Research, IT University of Copenhagen, Rued Langgaards Vej 7, 2300, Copenhagen S, Denmark

    Julian Togelius  & Georgios N. Yannakakis  & 

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Amoretti, M. (2011). A Design Framework for Ultra-Large-Scale Autonomic Systems. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2011. Lecture Notes in Computer Science, vol 6624. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20525-5_2

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  • DOI: https://doi.org/10.1007/978-3-642-20525-5_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20524-8

  • Online ISBN: 978-3-642-20525-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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