LSP and Back up Path Setup in MPLS Networks Based on Path Criticality Index Ali Tizghadam, Alberto Leon-Garcia Dept. of Electrical and Computer Engineering University of Toronto 40 St. George St., Toronto, ON, M5S 2E4, Canada {ali.tizghadam, alberto.leongarcia}@utoronto.ca Abstract— This paper reports on a promising approach for solving problems found when Multi Protocol Label Switching (MPLS), soon to be a dominant protocol, is used in core network systems. Difficulty is found largely in LSP routing and traffic engineering approaches. While there are a number of online and offline proposals to establish the LSPs but no one is a complete solution considering all the aspects of routing plan from traffic engineering point of view. Our research takes a viewpoint inspired by the concept of “between-ness” from graph theory, from which we introduce notions of link and path criticality indexes. The basis of the work is finding the most critical paths which are mathematically defined based on the algebra of routing. We try to avoid running aggregated flows or commodities on the most critical paths for the short term, and plan increasing the bandwidth of the critical paths for future if possible. This approach shows promise in simulations have run on benchmark networks available from research literature. Keywords- Flow Assignment; Graph Theory; MPLS; Quality of Service (QoS); Routing; Traffic Engineering I. INTRODUCTION The infrastructure of the traditional service provider is undergoing a fundamental transition from a telephone-service- focused circuit-switching architecture to a multi-service packet- switching architecture based on Internet Protocol (IP) and enhancements that enable Quality of Service and traffic engineering. IP transport networks that can transfer packets according to differentiated levels of QoS, availability and price are a key element to generating revenue through a rich offering of services and applications. In this shared infrastructure MPLS has a key role. In addition to providing a transparent intermediate layer to hide the complexity of the different data layer technologies from the higher layers, MPLS provides a flexible routing mechanism by assigning traffic flows to the end-to-end label switched paths (LSP). MPLS can be used to engineer the traffic among different paths of the network by intelligent matching of the path capacities with flows to avoid network congestion. An abundance of work has been done in the research community and industry to address the routing and flow assignment problem and traffic engineering issues in MPLS networks [1], [2], [3]. The main goal of the research reported in this paper is to look at the problem from another standpoint. Motivated by the definition of “between-ness” from graph theory [4], [5] we introduce the notion of link and path criticality indexes. The essence of the approach is to identify the most critical paths to avoid running the flows on these paths and try to set up LSPs and back up LSPs on less critical paths in the short-term as well as to plan to increase the bandwidth of the paths with high criticality index when possible. Our simulations on some benchmark networks discussed in the research literature show that the approach is promising. The paper organized as follows. Section II reviews the state of the art in MPLS routing and flow assignment problems. We describe the issues with existing methods and the associated research challenges. In section III, we introduce the mathematics and notions of algebraic routing based on [6] that allow us, in section IV, propose our path-criticality index-based routing scheme. Section V provides an extension to compute maximally disjoint back up paths. Section VI provides validation for our proposal. We assess our proposed method on some benchmark networks and present encouraging results. Finally we conclude with a discussion of open issues and future work. II. CURRENT STATE OF THE ART The most popular algorithm used in the research community for routing LSPs is the shortest path routing (SP). In this method the path with the least total number of links between source and destination (or the one with minimum overall weight when the links are weighted) is chosen. If there is more than one shortest path between source and destination, the algorithm is flexible, and one can choose a shortest path at random. Typically, the LSP setup algorithm keeps information about the residual capacity of each link, and when a new request comes, only the links with enough residual capacity are considered by the shortest path algorithm. While the shortest path algorithm enjoys the benefit of simplicity, it can cause major problems to the network due to the lack of any load balancing mechanism. Some links might become saturated while some remain underutilized. 1-4244-0353-7/07/$25.00 ©2007 IEEE This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the ICC 2007 proceedings.