Building Quality-of-Service Monitoring Systems for Traffic Engineering and Service Management
Journal of Network and Systems Management
Centralized channel assignment and routing algorithms for multi-channel wireless mesh networks
ACM SIGMOBILE Mobile Computing and Communications Review
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Toward a scalable and collaborative network monitoring overlay
TMA'11 Proceedings of the Third international conference on Traffic monitoring and analysis
A cooperative network monitoring overlay
NEW2AN'11/ruSMART'11 Proceedings of the 11th international conference and 4th international conference on Smart spaces and next generation wired/wireless networking
Monitoring, aggregation and filtering for efficient management of virtual networks
Proceedings of the 7th International Conference on Network and Services Management
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Network monitoring is an integral part of any network management system. In order to ensure end-to-end service quality stated in service level agreements (SLAs), managers of a service provider network need to gather quality-of-service (QoS) measurements from multiple nodes in the network. For a large network with over thousands of flows with end-to-end SLAs, the information exchanged between network nodes and a central network management system (NMS) could be substantial. We propose a mechanism called aggregation and refinement based monitoring (ARM) to reduce the amount of information exchange. ARM is a generic mechanism that can be configured to run with different objectives, including threshold-based, rank-based and percentile-based. The mechanism enables the NMS to collect data from network nodes using a dynamic QoS data aggregation/refinement technique, and to process these information differently depending on its measurement objective. Our simulation results show that for these various objectives, the selective refinement process is able to validate SLAs quickly, is an order of magnitude more efficient than a simple polling scheme, and performs well across a wide range of traffic loads