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Generalized Nash equilibria for SaaS/PaaS Clouds

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  • Anselmi, Jonatha
  • Ardagna, Danilo
  • Passacantando, Mauro

Abstract

Cloud computing is an emerging technology that allows to access computing resources on a pay-per-use basis. The main challenges in this area are the efficient performance management and the energy costs minimization.

Suggested Citation

  • Anselmi, Jonatha & Ardagna, Danilo & Passacantando, Mauro, 2014. "Generalized Nash equilibria for SaaS/PaaS Clouds," European Journal of Operational Research, Elsevier, vol. 236(1), pages 326-339.
  • Handle: RePEc:eee:ejores:v:236:y:2014:i:1:p:326-339
    DOI: 10.1016/j.ejor.2013.12.007
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    References listed on IDEAS

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    1. Bigi, Giancarlo & Castellani, Marco & Pappalardo, Massimo & Passacantando, Mauro, 2013. "Existence and solution methods for equilibria," European Journal of Operational Research, Elsevier, vol. 227(1), pages 1-11.
    2. Francisco Facchinei & Veronica Piccialli & Marco Sciandrone, 2011. "Decomposition algorithms for generalized potential games," Computational Optimization and Applications, Springer, vol. 50(2), pages 237-262, October.
    3. Francisco Facchinei & Christian Kanzow, 2010. "Generalized Nash Equilibrium Problems," Annals of Operations Research, Springer, vol. 175(1), pages 177-211, March.
    4. E. Cavazzuti & M. Pappalardo & M. Passacantando, 2002. "Nash Equilibria, Variational Inequalities, and Dynamical Systems," Journal of Optimization Theory and Applications, Springer, vol. 114(3), pages 491-506, September.
    5. Monderer, Dov & Shapley, Lloyd S., 1996. "Potential Games," Games and Economic Behavior, Elsevier, vol. 14(1), pages 124-143, May.
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    Cited by:

    1. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2018. "Co-residence based data vulnerability vs. security in cloud computing system with random server assignment," European Journal of Operational Research, Elsevier, vol. 267(2), pages 676-686.
    2. Jiawang Nie & Xindong Tang & Lingling Xu, 2021. "The Gauss–Seidel method for generalized Nash equilibrium problems of polynomials," Computational Optimization and Applications, Springer, vol. 78(2), pages 529-557, March.
    3. Chen, Li-Ming & Chang, Wei-Lun, 2020. "Under what conditions can an application service firm with in-house computing benefit from cloudbursting?," European Journal of Operational Research, Elsevier, vol. 282(1), pages 71-80.
    4. Migot, Tangi & Cojocaru, Monica-G., 2020. "A parametrized variational inequality approach to track the solution set of a generalized nash equilibrium problem," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1136-1147.
    5. Gabriella Colajanni & Patrizia Daniele, 2022. "A Mathematical Network Model and a Solution Algorithm for IaaS Cloud Computing," Networks and Spatial Economics, Springer, vol. 22(2), pages 267-287, June.
    6. Mauro Passacantando & Danilo Ardagna & Anna Savi, 2016. "Service Provisioning Problem in Cloud and Multi-Cloud Systems," INFORMS Journal on Computing, INFORMS, vol. 28(2), pages 265-277, May.
    7. Rodica Ioana Lung & Noémi Gaskó & Mihai Alexandru Suciu, 2020. "Pareto-based evolutionary multiobjective approaches and the generalized Nash equilibrium problem," Journal of Heuristics, Springer, vol. 26(4), pages 561-584, August.

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