An architecture for large scale Internet measurement
IEEE Communications Magazine
IEEE Communications Magazine
IEEE Journal on Selected Areas in Communications
A scalable monitoring approach based on aggregation and refinement
IEEE Journal on Selected Areas in Communications
NetScope: traffic engineering for IP networks
IEEE Network: The Magazine of Global Internetworking
RATES: a server for MPLS traffic engineering
IEEE Network: The Magazine of Global Internetworking
Enhancing QoS metrics estimation in multiclass networks
Proceedings of the 2007 ACM symposium on Applied computing
On the Performance and Scalability of Web Services for Monitoring MPLS-based Networks
Journal of Network and Systems Management
Providing cost-effective QoS monitoring in multiservice networks
NGI'09 Proceedings of the 5th Euro-NGI conference on Next Generation Internet networks
Toward reusable SLA monitoring capabilities
Software—Practice & Experience
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Deployment of quality-of-service (QoS) based value-added services in IP networks necessitates the use of traffic engineering. Traffic engineering allows service providers to use the network resources efficiently, according to the different quality levels associated with the range of services they offer. Traffic engineering relies typically on monitoring data for both “offline proactive” and “dynamic reactive” approaches. Monitoring data may be used for network provisioning, dynamic resource allocation, route management, and in-service performance verification for value-added IP services. A monitoring system should scale with the network size, the network speed, and the number of customers subscribed to use value-added IP services. This paper investigates the requirements of scalable monitoring system architectures, proposes principles for designing such systems and validates these principles through the design and implementation of a scalable monitoring system for traffic engineering and QoS delivery in IP Differentiated Services networks. Methods for assessing the relative merits of such monitoring systems are proposed. Experimental assessment results prove the scalability, accuracy, and also demonstrate the benefits of the proposed monitoring system.