Traffic Engineering and Path Protection in MPLS Virtual Private Networks

• Main Author: Aniker, Pooja S
• Other Authors: J. Ramanujam
• Format: Others
• Language: en
• Published: LSU 2005
• Subjects: Electrical & Computer Engineering
• Online Access: http://etd.lsu.edu/docs/available/etd-04122005-160920/

Traffic Engineering (TE) attempts to establish paths for the flow of data in a network so as to optimize the resource utilization and maximize the network performance. One of the main goals of Traffic Engineering is to bring about efficient and reliable network operations. Constraint based routing is the key to Multiprotocol label switching TE. Constraint based routing helps to manage traffic paths within a MPLS network and allows for traffic to flow along certain desired paths. MPLS also supports explicit routing thus providing TE capabilities. MPLS TE enables resiliency and reliability to be built into networks, thus increasing the value and availability of the network. TE is deployed in MPLS networks by providing TE extensions to interior gateway protocols like OSPF and IS-IS. MPLS creates a connection oriented model over the traditional connectionless framework of IP based networks. This connection oriented model helps to overcome several shortcomings of the IP network and also provide the necessary framework to give quality guarantees to IP traffic. Quality of Service (QoS) can be built into MPLS networks where TE is used. MPLS has made significant progress in recent years and is used for deployment of networks all over the world. In this thesis, we propose several constraint-based routing algorithms for MPLS based VPN's. Our algorithms support routing of both Quality of Service (QoS) and BE traffic over the MPLS network. We have implemented a route based and a link based approach for routing of QoS and BE traffic. We also implement the 1 + 1 and 1 : 1 link disjoint and node disjoint path protection mechanisms for the QoS traffic. We study the effect of the various parameters used in our equations such as epsilon, granularity, earning rate and hop count. The problem is formulated as a multicommodity flow (MCF) problem and is solved using the optimization tool - ILOG CPLEX. Our approach is scalable to large networks having a number of VPN's.