End-to-end optimal algorithms for integrated QoS, traffic engineering, and failure recovery
This paper addresses the problem of optimal quality of service (QoS), traffic engineering (TE) and failure recovery (FR) in computer networks by introducing novel algorithms that only use source inferrable information. More precisely, optimal data rate adaptation and load balancing laws are provided which are applicable to networks where multiple paths are available and multiple classes of service (CoS) are to be provided. Different types of multiple paths are supported, including point-to-point multiple paths, point-to-multipoint multiple paths, and multicast trees. In particular, it is shown that the algorithms presented only need a minimal amount of information for optimal control, i.e., whether a path is congested or not. Hence, the control laws provided in this paper allow source inferred congestion detection without the need for explicit congestion feedback from the network. The proposed approach is applicable to utility functions of a very general form and endows the network with the important property of robustness with respect to node/link failures; i.e., upon the occurrence of such a failure, the presented control laws reroute traffic away from the inoperative node/link and converge to the optimal allocation for the "reduced" network. The proposed control laws set the foundation for the development of highly scalable feature-rich traffic control protocols at the IP, transport, or higher layers with provable global stability and convergence properties.
optimization qos traffic engineering failure recovery distributed traffic control sliding mode control