Failure to thrive: QoS and the culture of operational networking
RIPQoS '03 Proceedings of the ACM SIGCOMM workshop on Revisiting IP QoS: What have we learned, why do we care?
Does Over-Provisioning Become More or Less Efficient as Networks Grow Larger?
ICNP '05 Proceedings of the 13TH IEEE International Conference on Network Protocols
NOX: towards an operating system for networks
ACM SIGCOMM Computer Communication Review
DevoFlow: cost-effective flow management for high performance enterprise networks
Hotnets-IX Proceedings of the 9th ACM SIGCOMM Workshop on Hot Topics in Networks
DevoFlow: scaling flow management for high-performance networks
Proceedings of the ACM SIGCOMM 2011 conference
Hot-ICE'12 Proceedings of the 2nd USENIX conference on Hot Topics in Management of Internet, Cloud, and Enterprise Networks and Services
Netshare and stochastic netshare: predictable bandwidth allocation for data centers
ACM SIGCOMM Computer Communication Review
Hierarchical policies for software defined networks
Proceedings of the first workshop on Hot topics in software defined networks
Participatory networking: an API for application control of SDNs
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
VMPatrol: dynamic and automated QoS for virtual machine migrations
Proceedings of the 8th International Conference on Network and Service Management
Corybantic: towards the modular composition of SDN control programs
Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks
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Network convergence is becoming increasingly important for cost reduction and management simplification. However, this convergence requires strict performance isolation while keeping fine-grained control of each service (e.g. VoIP, video conference etc.). It is difficult to guarantee the performance requirements for various serviceswith manual configuration of the Quality-of-Service (QoS) knobs on a per-device basis as is prevalent today. We propose a network QoS control framework for converged fabrics that automatically and flexibly programs a network of devices with the necessary QoS parameters, derived from a high level set of application requirements. The controller leverages our QoS extensions of OpenFlow APIs, including per-flow rate-limiters and dynamic priority assignment. We also present some results from a testbed implementation to validate the performance of our controller.