Simulated Annealing Based Bandwidth Reservation for QoS Routing

Numerous routing schemes have been reported to improve network performance over the years. Multi-path routing belongs to one of them and MPLS is an excellent platform for such routing. In this paper, the Shortest Distance Path Based Simulated Annealing (SDPSA) algorithm for finding optimal bandwidth reservation solutions for multi-path routing is developed to improve network performances. The algorithm, which employs the annealing method, is based on previous solutions to find the current sub-optimal solution for multi-path routing. Multiple objectives including balancing traffic load and minimizing network resource consumption are taken into consideration. Finally, the proposed algorithm is applied to a randomly generated network and the NSFNET network. The performance values are compared to a well-known multi-path routing algorithm-HSTwp. The simulation and comparison results show that the proposed SDPSA algorithm is feasible and efficient for the optimization of multi-path IP routing.

[1]  Yuekang Yang Chung-Horng Traffic Forecast in QoS Routing , 2022 .

[2]  Mikkel Thorup,et al.  Optimizing OSPF/IS-IS weights in a changing world , 2002, IEEE J. Sel. Areas Commun..

[3]  James C. Spall,et al.  Introduction to Stochastic Search and Optimization. Estimation, Simulation, and Control (Spall, J.C. , 2007 .

[4]  Zheng Wang,et al.  Explicit routing algorithms for Internet traffic engineering , 1999, Proceedings Eight International Conference on Computer Communications and Networks (Cat. No.99EX370).

[5]  Yanghee Choi,et al.  Traffic Engineering with Constrained Multipath Routing in MPLS Networks , 2004 .

[6]  Subhash Suri,et al.  Profile-based routing and traffic engineering , 2003, Comput. Commun..

[7]  J. Y. Yen Finding the K Shortest Loopless Paths in a Network , 1971 .

[8]  James C. Spall,et al.  Introduction to stochastic search and optimization - estimation, simulation, and control , 2003, Wiley-Interscience series in discrete mathematics and optimization.

[9]  Frank Kelly,et al.  Notes on effective bandwidths , 1994 .

[10]  Yaakov Kogan,et al.  Dimensioning bandwidth for elastic traffic in high-speed data networks , 2000, TNET.

[11]  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).

[12]  永井 豊,et al.  海外文献紹介 IEEE Communications Society Subject Matter Experts for Publication in the IEEE ICC 2006 Proceedings 特集 , 2008 .

[13]  Murali S. Kodialam,et al.  Minimum interference routing with applications to MPLS traffic engineering , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[14]  Konstantina Papagiannaki,et al.  Long-term forecasting of Internet backbone traffic: observations and initial models , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[15]  Jörg Liebeherr,et al.  Enhancing aggregate QoS through alternate routing , 2000, Globecom '00 - IEEE. Global Telecommunications Conference. Conference Record (Cat. No.00CH37137).

[16]  Ibrahim Matta,et al.  BRITE: an approach to universal topology generation , 2001, MASCOTS 2001, Proceedings Ninth International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems.