Abstract
Multi-Protocol Label Switching (MPLS) is a mechanism in high-performance telecommunications networks which directs and carries data from one network node to the next with the help of labels. MPLS makes it easy to create "virtual links" between distant nodes. It can encapsulate packets of various network protocols. MPLS is a highly scalable, protocol agnostic, data-carrying mechanism. Packet-forwarding decisions are made solely on the contents of this label, without the need to examine the packet itself. This allows one to create end-to-end circuits across any type of transport medium, using any protocol. There are high traffics when transmitting data in the MPLS Network due to emerging requirements of MPLS and associated internet usage. This paper proposes an Ant Colony Optimization (ACO) technique for traffic management in MPLS Network. ACO is a swarm intelligence methodology which offers highly optimized technique for dozen of engineering problems. In our proposed work, the ACO provides optimal value than existing algorithms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chou, C.T.: Traffic engineering for MPLS-based virtual private networks. Computer Networks 44, 319–333 (2004)
Srivastava, S., van de Liefvoort, A., Medhi, D.: Traffic engineering of MPLS backbone networks in the presence of heterogeneous streams. Computer Networks 53, 2688–2702 (2009)
Palmieri, F.: An MPLS-based architecture for scalable QoS and traffic engineering in converged multiservice mobile IP networks. Computer Networks 47, 257–269 (2005)
Boscoa, A., Bottab, A., Conteb, G., Iovannaa, P., Sabellaa, R., Salsanoc, S.: Internet like control for MPLS based traffic engineering: performance evaluation. Performance Evaluation 59, 121–136 (2005)
Iovanna, P., Sabella, R., Settembre, M.: Traffic engineering strategy for multi-layer networks based on the GMPLS paradigm. IEEE Netw. 17(2), 28–37 (2003)
Di Caro, G., Dorigo, M.: AntNet: A Mobile Agents Approach to Adaptive Routing. Tech. Rep. IRIDIA/97-12, Univ. Libre de Bruxelles, Brussels, Belgium (1997)
Schoonderwoerd, R., Holland, O., Bruten, J.: Ant like agents for load balancing in telecommunication networks. In: Proceedings of the First Int. Conf. on Autonomous Agents, pp. 9–216. ACM Press, New York (1997)
Duan, H., Yu, X.: Hybrid Ant Colony Optimization Using Memetic Algorithm for Traveling Salesman Problem. In: Proceedings of the IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning, pp. 92–95 (2007)
Subramanian, D., Druschel, P., Chen, J.: Ants and reinforcement learning: A case study in routing in dynamic networks. In: Proceedings of the 15th Int. Joint Conf. on Artificial Intelligence, pp. 823–838. Morgan Kaufmann, San Francisco (1997)
Sim, K.M., Sun, W.H.: Ant Colony Optimization for Routing and Load-Balancing: Survey and New Directions. IEEE Transactions on Systems, Man, and Cybernetics 33(5), 560–572 (2003)
Xing, L.-N., Chen, Y.-W., Wang, P., Zhao, Q.-S., Xiong, J.: A Knowledge-Based Ant Colony Optimization for Flexible Job Shop Scheduling Problems. Applied Soft Computing 10, 888–896 (2010)
Lopez-Ibanez, M., Blum, C.: Beam ACO for the traveling sales man problem with time windows. Computers & Operations Research 37, 1570–1583 (2010)
Chandra Mohan, B., Sandeep, R., Sridharan, D.: A Data Mining Approach for Predicting Reliable Path for Congestion Free Routing Using Self-motivated Neural Network. SCI, vol. 149, pp. 237–246. Springer, Heidelberg (2008)
Chandra Mohan, B., Baskaran, R.: Redundant Link Avoidance Algorithm for improving Network Efficiency. International Journal of Computer Science Issues 7(3) (May 2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rajagopalan, S., Naganathan, E.R., Raj, P.H. (2011). Ant Colony Optimization Based Congestion Control Algorithm for MPLS Network. In: Mantri, A., Nandi, S., Kumar, G., Kumar, S. (eds) High Performance Architecture and Grid Computing. HPAGC 2011. Communications in Computer and Information Science, vol 169. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22577-2_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-22577-2_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22576-5
Online ISBN: 978-3-642-22577-2
eBook Packages: Computer ScienceComputer Science (R0)