Optimal policy for label switched path setup in MPLS Networks

  • Authors:

  • T. Anjali;C. Scoglio;J. C. de Oliveira;I. F. Akyildiz;G. Uhl

  • Affiliations:

  • Broadband and Wireless Networking Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, 250, 14th Street, Atlanta, GA;Broadband and Wireless Networking Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, 250, 14th Street, Atlanta, GA;Broadband and Wireless Networking Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, 250, 14th Street, Atlanta, GA;Broadband and Wireless Networking Lab, School of Electrical and Computer Engineering, Georgia Institute of Technology, 250, 14th Street, Atlanta, GA;Swales Aerospace & NASA Goddard Space Flight Center, Beltsville, MD

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2002

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Abstract

An important aspect in designing a multiprotocol label switching (MPLS) network is to determine an initial topology and to adapt it to the traffic load. A topology change in an MPLS network occurs when a new label switched path (LSP) is created between two nodes. The LSP creation involves determining the route of the LSP and the according resource allocation to the path. A fully connected MPLS network can be used to minimize the signaling. The objective of this paper is to determine when an LSP should be created and how often it should be re-dimensioned. An optimal policy to determine and adapt the MPLS network topology based on the traffic load is presented. The problem is formulated as a continuous time Markov decision process with the objective to minimize the costs involving bandwidth, switching, and signaling. These costs represent the trade-off between utilization of network resources and signaling/processing load incurred on the network. The policy performs a filtering control to avoid oscillations which may occur due to highly variable traffic. The new policy has been evaluated by simulation and numerical results show its effectiveness and the according performance improvement. A sub-optimal policy is also presented which is less computationally intensive and complicated.