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Stigmergic Service Composition and Adaptation in Mobile Environments

  • Andrei PaladeEmail author
  • Christian Cabrera
  • Gary White
  • Siobhán Clarke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11236)

Abstract

Users within a limited geographic area can form service-sharing communities using the services deployed on their mobile devices. Creating Quality of Service (QoS) optimal service compositions in such decentralised and dynamic environments is challenging because of the service providers’ mobility and the inherent dynamism in the available services. Existing proposals for mobile environments either use template-matching composition or require a-priori knowledge about the QoS objectives’ weights, which limits the composition’s flexibility in such environments. This paper presents a stigmergic-based approach to model the decentralised, flexible and dynamic service interactions of providers in a mobile environment. A nature-inspired optimisation mechanism is used to approximate the set of QoS optimal compositions that result from these interactions. To facilitate adaptation of the composite during execution, we introduce a procedure that encourages the exploration of service composition configurations that emerge as a result of providers’ mobility. We evaluate the performance of the proposed approach with a no-adaptation variant, a Dijkstra-based, a Greedy and a Random approach. The results show that the proposed approach can obtain superior solutions compared with current optimisation methods for flexible service composition in mobile environments at the cost of increased overhead.

Keywords

Stigmergic Flexible QoS-aware service composition 

Notes

Acknowledgment

This work was funded by Science Foundation Ireland (SFI) under grant 13/IA/1885.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Andrei Palade
    • 1
    Email author
  • Christian Cabrera
    • 1
  • Gary White
    • 1
  • Siobhán Clarke
    • 1
  1. 1.School of Computer Science and StatisticsTrinity College DublinDublinIreland

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