A first course in fuzzy logic
Optimizing Quality of Service Using Fuzzy Control
DSOM '02 Proceedings of the 13th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Management Technologies for E-Commerce and E-Business Applications
A control-based middleware framework for quality-of-service adaptations
IEEE Journal on Selected Areas in Communications
Metric-based selection of timer methods for accurate measurements
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
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Internet service providers usually express the quality of network services through a set of values determined according to several network performance parameters periodically collected or measured. However, for common end-users, these values do not give an overall idea of the quality of the network services as they stand for different units and evaluate different perspectives of each service quality. In this context, this paper proposes the definition of a service-oriented unified metric which quantifies a global Quality of Service (QoS) indication by processing standard QoS parameters through a fuzzy controller. The proposed methodology, based on fuzzy logic and tested on Xfuzzy 3.0 platform, allows to close the gap between a high-level QoS perspective and the effective QoS measurements at lower protocolar levels. The definition of a single per-service QoS metric can be useful to simplify control tasks such as QoS routing, SLA negotiation and auditing.