A Bargaining Nash Game Based Adaptive Negotiation of Context Level Agreements for Pervasive Systems

  • Hayat RoutaibEmail author
  • Elarbi Badidi
  • Essaid Sabir
  • Mohammed ElKoutbi
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 366)


With the growing popularity of Internet-enabled devices, the impressive progress in sensing technology, and the adoption of cloud computing for provisioning services, users increasingly demand services that can adapt to their recent context. In this paper, we propose a multi-attributes and adaptive approach for Context Level Agreements (CLAs) negotiation between a context provider and a context consumer using a context broker. The approach employs a Nash bargaining model and evaluates the global utility of each party as a linear function of normalized Quality of Context (QoC) attributes during the rounds of negotiation. The ultimate goal is to improve context-based adaptation of context-aware applications and services. One of the advantages of this approach is that it permits to resolve conflicts of interests between the context provider and the context consumer when the global utility of each party reaches a Pareto optimum.


CLA QoC Nash bargaining Pareto optimum 


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  1. 1.
    Badidi, L., Esmahi, L.: A Cloud-based Approach for Context Information Provisioning. World of Computer Science and Information Technology Journal (WCSIT) 1, 63–70 (2011)Google Scholar
  2. 2.
    Maarouf, A., Marzouk, A., Haqiq, A., El Hamlaoui, M.: Towards a MDE approach for the establishment of a contract service level monitoring by third party in the cloud computing. In: Signal-Image Technology and Internet-Based Systems (SITIS), pp. 715–720 (2014)Google Scholar
  3. 3.
    Buchholz, T., Kpper, A., Schiffers, M.: Quality of context: what it is and why we need it? In: Proceedings of the 10th International Workshop of the HP OpenView University association (HPOVUA) (2003)Google Scholar
  4. 4.
    Copil, G., Moldovan, D., Salomie, I., et al.: Cloud SLA negotiation for energy saving - a particle swarm optimization approach. In: IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), pp. 289–296 (2012)Google Scholar
  5. 5.
    Muller, C., Resinas, M., Ruiz-Cortes, A.: Automated Analysis of Conflicts in WS-Agreement. IEEE Transactions Services Computing 7, 530–544 (2014)CrossRefGoogle Scholar
  6. 6.
    Katsuhide, F., Takayuki, I., Klein, M.: Finding nash bargaining solutions for multi-issue negotiations: a preliminary result. In: The 1st International Working Conference on Human Factors and Computational Models in Negotiation (HuCom 2008), pp. 63–70 (2008)Google Scholar
  7. 7.
    Kim, Y., Lee, K.: A quality measurement method of context information in ubiquitous environments. In: ICHIT 2006, pp. 576–581. IEEE Computer Society, Washington, DC (2006)Google Scholar
  8. 8.
    Manzoor, A., Truong, H.L., Dustdar, S.: Quality aware context information aggregation system for pervasive environments. In: International Conference on Advanced Information Networking and Applications Workshops (WAINA 2009), pp. 266–271 (2009)Google Scholar
  9. 9.
    Nash, J.F.: The bargaining problem. Econometrica 18, 155–162 (1950)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Bouterse, B., Perros, H., Thuente, D.: Multiobjective cloud capacity planning for time-varying customer demand. In: High-capacity Optical Networks and Emerging/Enabling Technologies (HONET), pp. 84–88 (2014)Google Scholar
  11. 11.
    Xianrong, Z., Martin, P., Powley, W., et al.: Applying bargaining game theory to web services negotiation. In: IEEE International Conference on Services Computing (SCC), pp. 218–225 (2010)Google Scholar
  12. 12.
    Badidi, E., Esmahi, L.: A Scalable Framework for Provisioning Context-aware Application Services with High-quality Context Information. The International Journal of ACM Jordan 1, 86–97 (2011)Google Scholar

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© Springer Science+Business Media Singapore 2016

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Authors and Affiliations

  • Hayat Routaib
    • 1
    Email author
  • Elarbi Badidi
    • 2
  • Essaid Sabir
    • 3
  • Mohammed ElKoutbi
    • 1
  1. 1.MIS Team, ENSIASMohammed V UniversityRabatMorocco
  2. 2.College of Information TechnologyUAE UniversityAl AinUAE
  3. 3.UBICOM Research Group, ENSEMHassan II UniversityCasablancaMorocco

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