Abstract
Network planning for existing as well as future high-speed networks is important for extracting best performance of networks. Network planning requires reliable traffic model which can serve constant as well as variable ingress traffic. In this paper, network performance is investigated with uniform and population-distance traffic models. Open Shortest Path First (OSPF) protocol is used for routing and link weight determination is a crucial task for this routing. Link weights in networks of different densities are optimized with an objective of minimizing network congestion. Ant Colony Optimization (ACO), Genetic Algorithm (GA) and Simulated Annealing (SAN) optimization techniques are applied to examine link weights of National Science Foundation NETwork (NSFNET) and standard COST 239 networks. The novelty of the work lies in investigations of network performance with different optimization techniques, traffic models and density. The outcome of this work can assist in optimizing overall network planning. Maximum latency and congestion of both networks are compared for each optimization and traffic model. It is observed that population-distance traffic modeling has reduced network congestion for both the networks but this traffic model has increased maximum latency of NSFNET. Performance of COST 239 network which is denser than NSFNET, has improved with population-distance traffic model w.r.t. congestion and latency.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Tune, P., Roughan, M.: Network-design sensitivity analysis. In: ACM International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2014, pp. 449–461 (2014). https://doi.org/10.1145/2591971.2591979. ISBN 978-1-4503-2789-3
Teixeira, R., Duffield, N., Rexford, J., Roughan, M.: Traffic matrix reloaded: impact of routing changes. In: Dovrolis, C. (ed.) PAM 2005. LNCS, vol. 3431, pp. 251–264. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-31966-5_20. ISBN 978-3-540-31966-5
Cisco document: best practices in core network capacity planning, C11-728551-00, pp. 1–11 (2013)
Pavon-Mariño, P.: net2plan 0.4.0 User’s Manual (2016)
Pavon-Mariño, P.: Optimization of Computer Networks—Modeling and Algorithms: A Hands-On Approach. Wiley, New York (2016)
Pavon-Mariño, P., Aparicio-Pardo, R., Moreno-Muñoz, G., Garcia-Haro, J., Veiga-Gontan, J.: MatPlanWDM: an educational tool for network planning in wavelength-routing networks. In: Tomkos, I., Neri, F., Solé Pareta, J., Masip Bruin, X., Sánchez Lopez, S. (eds.) ONDM 2007. LNCS, vol. 4534, pp. 58–67. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72731-6_7
Risso, C., Canale, E., Robledo, F., Rubino, G.: Using metaheuristics for planning resilient and cost-effective multilayer networks. In: 5th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), Almaty, pp. 201–207 (2013)
Martins, S.L., Ribeiro, C.C.: Metaheuristics and applications to optimization problems in telecommunications. In: Resende, M.G.C., Pardalos, P.M. (eds.) Handbook of Optimization in Telecommunications, pp. 103–128. Springer, Boston (2006). https://doi.org/10.1007/978-0-387-30165-5_4
Risso, C., Nesmachnow, S., Robledo, F.: Metaheuristic approaches for IP/MPLS network design. Int. Trans. Oper. Res. 25(2), 599–625 (2018)
Bhanja, U., Mahapatra, S.: A metaheuristic approach for optical network optimization problems. Appl. Soft Comput. 13, 981–997 (2013)
Kharroubi, F., He, J., Chen, L.: Performance analysis of GA, ROA, and TSA for solving the Max-RWA problem in optical networks, OFC 2014, San Francisco, CA, pp. 1–3 (2014). https://doi.org/10.1364/OFC.2014.W2A.48
Mohan, N., Wason, A., Sandhu, P.S.: ACO based single link failure recovery in all optical networks. Optik 127, 8469–8474 (2016)
Rabbani, M., Ravanbakhsh, M., Farrokhi-Asl, H., Taheri, M.: Using metaheuristic algorithms for solving a hub location problem: application in passive optical network planning. Int. J. Supply Oper. Manag. 4(1), 15–32 (2017)
Mata, J., et al.: Artificial intelligence (AI) methods in Optical Networks: A Comprehensive Survey. https://arxiv.org/abs/1801.01704v2 [cs.AI], Optical Switching and Networking (2018)
Network Simulator: Net2Plan. http://www.net2plan.com/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Saini, H., Garg, A.K. (2018). Investigations of Optimized Optical Network Performance Under Different Traffic Models. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_20
Download citation
DOI: https://doi.org/10.1007/978-981-13-1813-9_20
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1812-2
Online ISBN: 978-981-13-1813-9
eBook Packages: Computer ScienceComputer Science (R0)