Analysis of the increase and decrease algorithms for congestion avoidance in computer networks
Computer Networks and ISDN Systems
Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
A Class of End-to-End Congestion Control Algorithms for the Internet
ICNP '98 Proceedings of the Sixth International Conference on Network Protocols
Adaptive algorithms for feedback-based flow control in high-speed, wide-area ATM networks
IEEE Journal on Selected Areas in Communications
The rate-based flow control framework for the available bit rate ATM service
IEEE Network: The Magazine of Global Internetworking
Optimal flow control and routing in multi-path networks
Performance Evaluation - Special issue: Internet performance and control of network systems
Empirical study of traffic trunking in Linux-based MPLS test-bed
International Journal of Network Management
Adaptive control algorithms for decentralized optimal traffic engineering in the internet
IEEE/ACM Transactions on Networking (TON)
Stochastic traffic engineering for demand uncertainty and risk-aware network revenue management
IEEE/ACM Transactions on Networking (TON)
An integrated, distributed traffic control strategy for the future internet
Proceedings of the 2006 SIGCOMM workshop on Internet network management
Overlay routing with acceptable waiting time for unstably fluctuated network environments
ICOIN'09 Proceedings of the 23rd international conference on Information Networking
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Distributed optimal traffic engineering in the presence of multiple paths has been found to be a difficult problem to solve. In this paper, we introduce a new approach in an attempt to tackle this problem. This approach has its basis in nonlinear control theory. More precisely, it relies on the concept of Sliding Modes. We develop a family of control laws, each of them having the property that the steady-state network resource allocation yields the maximum of the given utility function, subject to the network resource constraints. These control laws not only allow each ingress node to independently adjust its traffic sending rate but also provide a scheme for optimal traffic load redistribution among multiple paths. The only nonlocal information needed is binary feedback from each congested node in the path. Moreover, the algorithms presented are applicable to a large class of utility functions, namely, utility functions that can be expressed as the sum of concave functions of the sending rates. We show that the technique can be applied not only to rate adaptive traffic with multiple paths, but also to assured service traffic with multiple paths. Preliminary case studies show that this technique is potentially very useful for optimal traffic engineering in a multiple-class-of-service and multiple-path enabled Internet, e.g., differentiated services enabled multi-protocol label switching networks.