Host selection through collective decision

  • Authors:
  • Fabrice Saffre;Aistis Simaitis

  • Affiliations:
  • ETISALAT BT Innovation Centre, Khalifa University, Dhabi, UAE;University of Oxford, UK

  • Venue:
  • ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special section on formal methods in pervasive computing, pervasive adaptation, and self-adaptive systems: Models and algorithms
  • Year:
  • 2012

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Abstract

In this article, we present a collective decision-making framework inspired by biological swarms and capable of supporting the emergence of a consensus within a population of agents in the absence of environment-mediated communication (stigmergy). Instead, amplification is the result of the variation of a confidence index, stored in individual memory and providing each agent with a statistical estimate of the current popularity of its preferred choice within the whole population. We explore the fundamental properties of our framework using a combination of analytical and numerical methods. We then use Monte Carlo simulation to investigate its applicability to host selection in the presence of multiple alternatives, a problem found in application migration scenarios. The advantages of self-organization and the use of statistically predictive methods in this context are also discussed.