Multi-agent selection of multiple composite web services based on CBR method and driven by QoS

Siala, Fatma; Lajmi, Soufiene; Ghédira, Khaled

doi:10.1145/2095536.2095554

Cited by 5 publications

(1 citation statement)

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“…A new negotiation protocol was also presented to support coordinated negotiation. A framework was presented to select composite services by a multi-agent system using a case-based reasoning method [26], [27]. The authors of [8] introduced an approach for the Web service selection problem with large scale processes and severe QoS constraints.…”

Section: Related Workmentioning

confidence: 99%

Multi-Phase Ant Colony System for Multi-Party Data-Intensive Service Provision

Wang

Shen

2016

IEEE Trans. Serv. Comput.

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The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism is considered in this paper. We exploit a group of agents automatically negotiating to establish agreeable service contracts. Twostage negotiation procedures are used in our data-intensive service provision model, which will provide effective and efficient service selection for service composers. We also present a multi-phase, multi-party negotiation protocol, where the ant colony system is applied to select services with the best or near-optimal utility outputs. In order to adapt the ant colony system to handle the dynamic scenarios during negotiations, we also discuss several strategies for modifying the pheromone information in the first place. The experimental results show that our negotiation-based approach can facilitate the data-intensive service provision with better outcome. University of Wollongong, NSW, Australia E-mail: lw840@uowmail.edu.au, jshen@uow.edu.au ! Abstract-The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism is considered in this paper. We exploit a group of agents automatically negotiating to establish agreeable service contracts. Two-stage negotiation procedures are used in our data-intensive service provision model, which will provide effective and efficient service selection for service composers. We also present a multi-phase, multi-party negotiation protocol, where the ant colony system is applied to select services with the best or near-optimal utility outputs. In order to adapt the ant colony system to handle the dynamic scenarios during negotiations, we also discuss several strategies for modifying the pheromone information in the first place. The experimental results show that our negotiation-based approach can facilitate the data-intensive service provision with better outcome.

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Section: Related Workmentioning

confidence: 99%