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Gaussian-Based Bidding Strategies for Service Composition Simulations

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Recent Advances in Agent-based Complex Automated Negotiation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 638))

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Abstract

Service composition plays a crucial role in service–oriented computing allowing to deliver complex distributed applications obtained by aggregating autonomous and independent component services characterized by a given functionality and a Quality of Service. Automated negotiation is a viable approach to select component services according to their QoS values so to meet the end–to–end quality requirements of users requesting the application. This paper discusses the use of Gaussian probability functions to model negotiation strategies of service providers, and how the properties of these functions can be used to model multiple negotiations necessary for service composition as a single multi–issue negotiation. A numerical analysis shows comparable negotiation trends for the different representations of the service composition problem.

Ph.D. scholarship funded by Media Motive S.r.l, POR Campania FSE 2007–2013.

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Acknowledgments

The research leading to these results has received funding from the EU FP7-ICT-2012-8 under the MIDAS Project (Model and Inference Driven - Automated testing of Services architectures), Grant Agreement no. 318786, and the Italian Ministry of University and Research and EU under the PON OR.C.HE.S.T.R.A. project (ORganization of Cultural Heritage for Smart Tourism and Real-time Accessibility).

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Authors and Affiliations

  1. Dipartimento di Ingegneria Elettrica e Tecnologie dell’Informazione, University of Naples “Federico II”, Napoli, Italy

    Silvia Rossi

  2. Dipartimento di Matematica, University of Naples “Federico II”, Napoli, Italy

    Dario Di Nocera

  3. Istituto di Calcolo e Reti ad Alte Prestazioni—C.N.R., Via P. Castellino 111, 80131, Naples, Italy

    Claudia Di Napoli

Authors
  1. Silvia Rossi
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  2. Dario Di Nocera
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  3. Claudia Di Napoli
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Corresponding author

Correspondence to Silvia Rossi .

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Editors and Affiliations

  1. Hamamatsu, Shizuoka, Japan

    Naoki Fukuta

  2. Nagoya Institute of Technology, Nagoya, Japan

    Takayuki Ito

  3. School of Computer Science, University of Wollongong, Wollongong, New South Wales, Australia

    Minjie Zhang

  4. Tokyo University of Agriculture and, Tokyo, Japan

    Katsuhide Fujita

  5. Institute of Sensors, Signals, Heriot-Watt University, Riccarton, United Kingdom

    Valentin Robu

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Rossi, S., Di Nocera, D., Di Napoli, C. (2016). Gaussian-Based Bidding Strategies for Service Composition Simulations. In: Fukuta, N., Ito, T., Zhang, M., Fujita, K., Robu, V. (eds) Recent Advances in Agent-based Complex Automated Negotiation. Studies in Computational Intelligence, vol 638. Springer, Cham. https://doi.org/10.1007/978-3-319-30307-9_12

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  • DOI: https://doi.org/10.1007/978-3-319-30307-9_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30305-5

  • Online ISBN: 978-3-319-30307-9

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