Analytical framework for dynamic traffic partitioning in MPLS networks

Internet traffic engineering is concerned with the performance optimization of IP networks. Multiprotocol Label Switching (MPLS) is an important technology that supports the Internet traffic engineering function. This paper considers a network performance optimization problem related to traffic engineering over MPLS. We investigate the use of a dynamic traffic partitioning and assignment methodology to adaptively map ingress traffic into several parallel Label Switched Paths (LSPs) in MPLS based IP networks. We present a stochastic framework for the traffic partitioning problem. Within this framework, a set of parallel edge disjoint LSPs is modeled by parallel queues and a partitioning algorithm is devised for different service classes that is adaptive to the prevailing state of the network. The performance of this approach is illustrated with numerical examples