Abstract-Multiprotocol Label Switching or MPLS technology is being increasingly deployed by several of the largest Internet service providers to solve problems such as traffic engineering and to offer IP services like Virtual Private Networks (VPNs). In MPLS, the analysis of the packet (network layer) header is performed just once, and each packet is assigned a stack of labels, which is examined by subsequent routers when making forwarding decisions. Despite the fact that MPLS is becoming widespread on the Internet, we know essentially very little about the performance one can achieve with it, and about the intrinsic trade-offs in its use of resources. In this paper, we undertake a comprehensive study of the label size versus stack depth trade-off for MPLS routing protocols on lines and trees. We show that in addition to LSP tunneling, label stacks can also be used to dramatically reduce the number of labels required for setting up MPLS LSPs in a network. Based on this observation, we develop routing algorithms and prove lower bounds for two basic problems: (1) FIXED LABEL ROUTING: Given a fixed number of labels, we want to minimize the stack depth, and (2) FIXED STACK ROUTING: Given a bound on the stack depth, we want to minimize the number of labels used. Our simulation results validate our approach, demonstrating that our novel protocols enable MPLS routing on large trees with few labels and small stack sizes. Thus, our MPLS routing algorithms are applicable to a number of practical scenarios involving the provisioning of VPNs and multicast trees.
In REF , a comprehensive study of label size versus stack depth trade-off for MPLS routing protocols on lines and trees is undertaken.
Exploring the trade-off between label size and stack depth in MPLS routing
IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428)
IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428)
Computer Science