Abstract

Traffic Engineering (TE) is one of the keys for improving packet forwarding in the Internet. It allows IP network operators to finely tune their forwarding paths according to various customer needs. One of the most popular tool available today for optimizing the use of networking resources is MPLS. On the one hand, operators may use MPLS and label distribution mechanisms such as RSVP-TE in conjunction with BGP to define multiple transit paths (for a given edge pair) verifying different constraints on their network. On the other hand, when operators simply enable LDP for distributing MPLS labels in order to improve the scalability of their network, another kind of path diversity may appear thanks to the ECMP feature of IGP routing. In this paper, using an MPLS labels analysis, we demonstrate that it is possible to better understand the transit path diversity deployed within a given ISP. More specifically, we introduce the Label Pattern Recognition (LPR) algorithm, a method for analyzing traceroute data including MPLS information. LPR reveals the actual usage of MPLS according to the inferred label distribution protocol and is able to make the distinction between ECMP and TE multi-path forwarding. Based on an extensive and longitudinal traceroute dataset obtained from CAIDA, we apply LPR and find that each ISP behavior is really specific in regard to its MPLS usage. In particular, we are able to observe independently for each ISP the MPLS path diversity and usage, and its evolution over time. Globally speaking, the main outcomes of our study are that (i) the usage of MPLS has been increasing over the the last five years with basic encapsulation being predominant, (ii) path diversity is mainly provided thanks to ECMP and LDP, and, (iii), TE using MPLS is as common as MPLS without path diversity. Peer reviewed