IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v73y2020i2d10.1007_s11235-019-00606-3.html
   My bibliography  Save this article

Interconnecting networks with optimized service provisioning

Author

Listed:
  • Abdul Basit

    (National University of Sciences and Technology)

  • Saad Qaisar

    (National University of Sciences and Technology)

  • Mudassar Ali

    (National University of Sciences and Technology
    University of Engineering and Technology, Taxila)

  • Muhammad Naeem

    (COMSATS University Islamabad, Wah Campus)

  • Marc Bruyere

    (Internet Initiative Japan Institute of Innovation)

  • Joel J. P. C. Rodrigues

    (Federal University of Piauí
    Instituto de Telecomunicações)

Abstract

A recent trend of peering at geo-diversified Internet exchange points (IXPs) has empowered decades-old proposal of inter-networking and opened up new avenues of business ventures. IP-transit, cloud direct and remote peering are a few important amongst numerous proposals of service provisioning capitalizing on this peering infrastructure support across domains. Enduring these business proposals becomes a challenging task, especially when the increased dependency of enterprises over the Internet is affirmed. Volatile traffic priorities necessitate different strategies of flow management for each pattern of enterprise traffic. Providing diverse service guarantees to each traffic class require careful selection of resource allocation and compliance of inter-domain policies. In this paper, we propose a novel orchestration framework that helps to stitch end-to-end traffic engineering compliant multiple paths. The framework enables prioritized management of various traffic classes in a centralized manner by employing software defined networking paradigm. Abstraction of multi-graph from the inter-connectivity of peering anchors helps to gear service provisioning spanning across multiple domains. Beside presenting details of our framework, we have articulated use cases highlighting the efficacy of our proposal. We have observed a maximum increase of 26.52% in throughput using proposed model compared with an optimization formulation from literature. Our results imply transparent utility of this formulation for various network topologies and traffic loads.

Suggested Citation

  • Abdul Basit & Saad Qaisar & Mudassar Ali & Muhammad Naeem & Marc Bruyere & Joel J. P. C. Rodrigues, 2020. "Interconnecting networks with optimized service provisioning," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 73(2), pages 223-239, February.
    • Handle: RePEc:spr:telsys:v:73:y:2020:i:2:d:10.1007_s11235-019-00606-3
    DOI: 10.1007/s11235-019-00606-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-019-00606-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-019-00606-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. E. L. Lawler & M. D. Bell, 1966. "A Method for Solving Discrete Optimization Problems," Operations Research, INFORMS, vol. 14(6), pages 1098-1112, December.
    2. Robert Fourer & David M. Gay & Brian W. Kernighan, 1990. "A Modeling Language for Mathematical Programming," Management Science, INFORMS, vol. 36(5), pages 519-554, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sinha, Ankur & Rämö, Janne & Malo, Pekka & Kallio, Markku & Tahvonen, Olli, 2017. "Optimal management of naturally regenerating uneven-aged forests," European Journal of Operational Research, Elsevier, vol. 256(3), pages 886-900.
    2. Duck Bong Kim, 2019. "An approach for composing predictive models from disparate knowledge sources in smart manufacturing environments," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1999-2012, April.
    3. Vaz, A. Ismael F. & Fernandes, Edite M. G. P. & Gomes, M. Paula S. F., 2004. "Robot trajectory planning with semi-infinite programming," European Journal of Operational Research, Elsevier, vol. 153(3), pages 607-617, March.
    4. Cindy Paola Guzman & Nataly Bañol Arias & John Fredy Franco & Marcos J. Rider & Rubén Romero, 2020. "Enhanced Coordination Strategy for an Aggregator of Distributed Energy Resources Participating in the Day-Ahead Reserve Market," Energies, MDPI, vol. 13(8), pages 1-22, April.
    5. Yongyang Cai & Kenneth L. Judd, 2023. "A simple but powerful simulated certainty equivalent approximation method for dynamic stochastic problems," Quantitative Economics, Econometric Society, vol. 14(2), pages 651-687, May.
    6. Fátima Pilar & Eliana Costa e Silva & Ana Borges, 2023. "Optimizing Vehicle Repairs Scheduling Using Mixed Integer Linear Programming: A Case Study in the Portuguese Automobile Sector," Mathematics, MDPI, vol. 11(11), pages 1-23, June.
    7. Cai, Yongyang & Judd, Kenneth L., 2012. "Dynamic programming with shape-preserving rational spline Hermite interpolation," Economics Letters, Elsevier, vol. 117(1), pages 161-164.
    8. Castagna, Andrés & Matonte, Federico & Mauttone, Antonio & Rodríguez-Gallego, Lorena & Blumetto, Oscar, 2024. "Land use planning to minimize the export of phosphorus: An optimization model for dairy production at a catchment area scale," Land Use Policy, Elsevier, vol. 138(C).
    9. Resteanu, Cornel & Filip, Florin-Gheorghe & Stanescu, Sorin & Ionescu, Cezar, 2000. "A cooperative production planning method in the field of continuous process plants," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 65-78, March.
    10. D. K. Karpouzos & K. L. Katsifarakis, 2021. "A new benchmark optimization problem of adaptable difficulty: theoretical considerations and practical testing," Operational Research, Springer, vol. 21(1), pages 231-250, March.
    11. Rao, Harish Venkatesh & Dutta, Goutam & Basu, Sankarshan, 2014. "Database Structure for a Multi Stage Stochastic Optimization Based Decision Support System for Asset – Liability Management of a Life Insurance Company," IIMA Working Papers WP2014-06-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    12. Gordon P. Wright & Alok R. Chaturvedi & Radha V. Mookerjee & Susan Garrod, 1998. "Integrated Modeling Environments in Organizations: An Empirical Study," Information Systems Research, INFORMS, vol. 9(1), pages 64-84, March.
    13. Yongyang Cai & Kenneth Judd, 2015. "Dynamic programming with Hermite approximation," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 81(3), pages 245-267, June.
    14. Kıbış, Eyyüb Y. & Büyüktahtakın, İ. Esra, 2017. "Optimizing invasive species management: A mixed-integer linear programming approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 308-321.
    15. Joel Goh & Melvyn Sim, 2011. "Robust Optimization Made Easy with ROME," Operations Research, INFORMS, vol. 59(4), pages 973-985, August.
    16. Robert Fourer & David M. Gay, 2002. "Extending an Algebraic Modeling Language to Support Constraint Programming," INFORMS Journal on Computing, INFORMS, vol. 14(4), pages 322-344, November.
    17. Michael R. Bussieck & Michael C. Ferris & Alexander Meeraus, 2009. "Grid-Enabled Optimization with GAMS," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 349-362, August.
    18. Dutta, Goutam & Natesan, Sumeetha R. & Thakur, Deepika & Tiwari, Manoj K., 2020. "A Mathematical Programming Approach with Revenue Management in Home Loan Pricing (Revised as on 20-12-2021)," IIMA Working Papers WP 2020-02-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    19. Yongyang Cai & Kenneth Judd, 2013. "Shape-preserving dynamic programming," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 407-421, June.
    20. Guillermo Cabrera-Guerrero & Andrew J. Mason & Andrea Raith & Matthias Ehrgott, 2018. "Pareto local search algorithms for the multi-objective beam angle optimisation problem," Journal of Heuristics, Springer, vol. 24(2), pages 205-238, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:73:y:2020:i:2:d:10.1007_s11235-019-00606-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.