In this paper, we propose a novel traffic engineering architecture for IP networks with MPLS backbones. In this architecture, two link-disjoint label switched paths, namely the primary and secondary paths, are established among every pair of IP routers located at the edges of an MPLS backbone network. As the main building block of this architecture, we propose that primary paths are given higher priority against the secondary paths in the MPLS data plane to cope with the so-called knock-on effect. Inspired by the ABR flow control mechanism in ATM networks, we propose to split traffic between a source-destination pair between the primary and secondary paths using explicit rate feedback from the network. Taking into consideration the performance deteriorating impact of packet reordering in packet-based load balancing schemes, we propose a traffic splitting mechanism that operates on a per-flow basis (i.e., flow-based multipath routing). We show via an extensive simulation study that using flow-based multipath traffic engineering with explicit rate feedback not only provides consistently better throughput than that of a single path but is also void of out-of-order packet delivery.

In this paper we study traffic engineering in Multiprotocol Label Switching (MPLS) networks. We consider off-line computation of disjoint working and restoration paths where path rerouting is used as the restoration scheme. We first compute maximum number of paths for each demand such that paths satisfy diversity requirements. Using the generated path set we study four different approaches for selecting working and restoration paths, and formulate each method as an Integer Linear Programming (ILP) problem. The first two methods treat working and restoration path design problems separately. We propose two new path design methods that jointly optimize the working and restoration paths. A traffic uncertainty model is developed in order to evaluate performances of these four approaches based on their robustness with respect to changing traffic patterns. We compare these design approaches based on the number of additional demands carried and the distribution of residual capacity over the network. It is shown through simulations that the weighted load balancing method proposed in this paper outperforms the other three methods in handling traffic demand uncertainty.