Parallel LSPs for constraint-based routing and load balancing in MPLS networks

Two features of multiprotocol label switching are very useful in network traffic engineering: the path-oriented nature, and the capability to support multiple paths between an ingress-egress node pair. The first feature makes it easy to adaptively route traffic through the network based on the load condition in different parts of the network, while the second feature is often used for load balancing. The role of parallel label-switched paths (LSP) in load balancing and constraint-based routing is investigated. An algorithm named parallel-path-based bandwidth scheme (PPBS) is proposed to make use of parallel LSPs in choosing a bandwidth constraint path. The improvement on flow blocking probability by using PPBS is given quantitatively with respect to the average traffic load on the link, the hops along the path, and the possible number of parallel paths. In conjunction with the PPBS scheme, a feedback-based load-balancing algorithm (FBLB) is proposed to properly distribute traffic onto the parallel LSPs determined by the PPBS. This FBLB algorithm relies on the signalling packets to convey network status information back to the source. Consequently the sources can adjust the traffic dis tribution into each LSP accurately and promptly. Simulation results show that the FBLB algorithm is simple and effective.

[1]  Anwar Elwalid,et al.  Exploiting parallelism to boost data-path rate in high-speed IP/MPLS networking , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[2]  Daniel O. Awduche,et al.  Requirements for Traffic Engineering Over MPLS , 1999, RFC.

[3]  Klara Nahrstedt,et al.  An overview of quality of service routing for next-generation high-speed networks: problems and solutions , 1998, IEEE Netw..

[4]  Ariel Orda,et al.  QoS routing in networks with inaccurate information: theory and algorithms , 1999, TNET.

[5]  Angela L. Chiu,et al.  Overview and Principles of Internet Traffic Engineering , 2002, RFC.

[6]  Mikkel Thorup,et al.  Internet traffic engineering by optimizing OSPF weights , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[7]  Oliver W. W. Yang,et al.  Delay-based adaptive load balancing in MPLS networks , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[8]  Roberto Battiti,et al.  A Reactive Scheme for Traffic Engineering in MPLS Networks , 2002 .

[9]  Keping Long,et al.  Load balancing algorithms in MPLS traffic engineering , 2001, 2001 IEEE Workshop on High Performance Switching and Routing (IEEE Cat. No.01TH8552).

[10]  Anja Feldmann,et al.  NetScope: traffic engineering for IP networks , 2000, IEEE Netw..

[11]  Qiong Wang,et al.  Stochastic traffic engineering, with applications to network revenue management , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[12]  Atsushi Iwata,et al.  A hierarchical multilayer QoS routing system with dynamic SLA management , 2000, IEEE Journal on Selected Areas in Communications.

[13]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[14]  Cheng Jin,et al.  MATE: MPLS adaptive traffic engineering , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[15]  Ariel Orda,et al.  QoS Routing Mechanisms and OSPF Extensions , 1999, RFC.