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A Reinforcement Learning Approach to Adaptive Forwarding in Named Data Networking

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Computer and Information Sciences (ISCIS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 935))

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Abstract

This paper addresses Information Centric Networks, and considers in-network caching for Named Data Networking (NDN) architectures. We depart from forwarding algorithms which primarily use links that have been selected by the routing protocol for probing and forwarding, and propose an adaptive forwarding strategy using reinforcement learning with the random neural network (NDNFS-RLRNN), to leverage the routing information and actively seek possible deliveries outside these paths in a controlled way. Our simulations show that NDNFS-RLRNN achieves more efficient delivery performance than a strategy that strictly follows the routing layer or a strategy that retrieves contents from the nearest caches by flooding requests.

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References

  1. Xylomenos, G., et al.: A survey of information-centric networking research. IEEE Commun. Surv. Tutor. 16(2), 1024–1049 (2014)

    Article  Google Scholar 

  2. Cisco, V.: Cisco visual networking index: forecast and methodology, 2016–2021 (2017)

    Google Scholar 

  3. Zhang, L., et al.: Named data networking. SIGCOMM Comput. Commun. Rev. 44(3), 66–73 (2014)

    Article  Google Scholar 

  4. Lehman, V., et al.: An experimental investigation of hyperbolic routing with a smart forwarding plane in NDN. In: 2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS), pp. 1–10 (2016)

    Google Scholar 

  5. Jacobson, V., Smetters, D.K., Thornton, J.D., Plass, M.F., Briggs, N.H., Braynard, R.L.: Networking named content. In: Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies, CoNEXT 2009, pp. 1–12. ACM, New York, USA (2009)

    Google Scholar 

  6. Afanasyev, A., et al.: NFD developer’s guide. Technical Report NDN-0021, Department of Computer Science, University of California, Los Angeles, USA (2014)

    Google Scholar 

  7. Yi, C., Afanasyev, A., Wang, L., Zhang, B., Zhang, L.: Adaptive forwarding in named data networking. SIGCOMM Comput. Commun. Rev. 42(3), 62–67 (2012)

    Article  Google Scholar 

  8. Garcia-Luna-Aceves, J., Mirzazad-Barijough, M.: Enabling correct interest forwarding and retransmissions in a content centric network. In: Proceedings of the Eleventh ACM/IEEE Symposium on Architectures for Networking and Communications Systems, ANCS 2015, pp. 135–146. IEEE Computer Society, Washington, USA (2015)

    Google Scholar 

  9. Gelenbe, E.: Self-aware networks: the cognitive packet network and its performance. In: Kounev, S., Kephart, J., Milenkoski, A., Zhu, X. (eds.) Self-Aware Computing Systems, pp. 659–668. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-47474-8_23

    Chapter  Google Scholar 

  10. Gelenbe, E., Fourneau, J.M.: Random neural networks with multiple classes of signals. Neural Comput. 11(4), 953–963 (1999)

    Article  Google Scholar 

  11. Gelenbe, E.: Steps toward self-aware networks. Commun. ACM 52(7), 66–75 (2009)

    Article  Google Scholar 

  12. Birke, R.: Self-aware computing systems: open challenges and future research directions. In: Kounev, S., Kephart, J., Milenkoski, A., Zhu, X. (eds.) Self-Aware Computing Systems, pp. 709–722. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-47474-8_26

    Chapter  Google Scholar 

  13. Rossini, G., Rossi, D.: Coupling caching and forwarding: benefits, analysis, and implementation. In: Proceedings of the 1st ACM Conference on Information-Centric Networking, ACM-ICN 2014, pp. 127–136. ACM, New York, USA (2014)

    Google Scholar 

  14. Yi, C., Afanasyev, A., Moiseenko, I., Wang, L., Zhang, B., Zhang, L.: A case for stateful forwarding plane. Comput. Commun. 36(7), 779–791 (2013)

    Article  Google Scholar 

  15. Qian, H., Ravindran, R., Wang, G.Q., Medhi, D.: Probability-based adaptive forwarding strategy in named data networking. In: 2013 IFIP/IEEE International Symposium on Integrated Network Management (IM 2013), pp. 1094–1101 (2013)

    Google Scholar 

  16. Nguyen, D., Fukushima, M., Sugiyama, K., Tagami, A.: Efficient multipath forwarding and congestion control without route-labeling in CCN. In: 2015 IEEE International Conference on Communication Workshop (ICCW), pp. 1533–1538 (2015)

    Google Scholar 

  17. Posch, D., Rainer, B., Hellwagner, H.: SAF: stochastic adaptive forwarding in named data networking. IEEE/ACM Trans. Netw. 25(2), 1089–1102 (2017)

    Article  Google Scholar 

  18. Chiocchetti, R., Perino, D., Carofiglio, G., Rossi, D., Rossini, G.: Inform: a dynamic interest forwarding mechanism for information centric networking. In: Proceedings of the 3rd ACM SIGCOMM Workshop on Information-Centric Networking, ICN 2013, pp. 9–14. ACM, New York, USA (2013)

    Google Scholar 

  19. Boyan, J.A., Littman, M.L.: Packet routing in dynamically changing networks: a reinforcement learning approach. In: Proceedings of the 6th International Conference on Neural Information Processing Systems, NIPS 1993, pp. 671–678. Morgan Kaufmann Publishers Inc., San Francisco, USA (1993)

    Google Scholar 

  20. Gelenbe, S.E.: Cognitive packet network. US Patent No. 6804201 (2004)

    Google Scholar 

  21. Gelenbe, E.: Réseaux neuronaux aléatoires stables. Comptes-rendus de l’Académie des Sciences. Série 2, Mécanique, Physique, Chimie, Sciences de l’Univers. Sciences de la Terre 310(3), 177–180 (1990)

    Google Scholar 

  22. Halici, U.: Reinforcement learning with internal expectation for the random neural network. Eur. J. Oper. Res. 126(2), 288–307 (2000)

    Article  MathSciNet  Google Scholar 

  23. Gelenbe, E., Lent, R.: Power-aware ad hoc cognitive packet networks. Ad Hoc Netw. 2(3), 205–216 (2004)

    Article  Google Scholar 

  24. Sakellari, G.: The cognitive packet network: a survey. Comput. J. 53(3), 268 (2010)

    Article  Google Scholar 

  25. Gelenbe, E., Liu, P., Lainé, J.: Genetic algorithms for route discovery. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 36(6), 1247–1254 (2006)

    Article  Google Scholar 

  26. Wang, L., Gelenbe, E.: Adaptive dispatching of tasks in the cloud. IEEE Trans. Cloud Comput. 6(1), 33–45 (2018)

    Article  Google Scholar 

  27. Mastorakis, S., Afanasyev, A., Moiseenko, I., Zhang, L.: ndnSIM 2: an updated NDN simulator for NS-3. Technical Report NDN-0028, Revision 2, NDN (2016)

    Google Scholar 

  28. Knight, S., Nguyen, H., Falkner, N., Bowden, R., Roughan, M.: The internet topology zoo. IEEE J. Sel. Areas Commun. 29(9), 1765–1775 (2011)

    Article  Google Scholar 

  29. Chai, W.K., He, D., Psaras, I., Pavlou, G.: Cache “less for more” in information-centric networks (extended version). Comput. Commun, 36(7), 758–770 (2013)

    Article  Google Scholar 

  30. Psaras, I., Chai, W.K., Pavlou, G.: Probabilistic in-network caching for information-centric networks. In: Proceedings of the Second Edition of the ICN Workshop on Information-Centric Networking, ICN 2012, pp. 55–60. ACM, New York, USA (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Imperial College London, London, UK

    Olumide Akinwande & Erol Gelenbe

Authors
  1. Olumide Akinwande
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  2. Erol Gelenbe
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Corresponding author

Correspondence to Olumide Akinwande .

Editor information

Editors and Affiliations

  1. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland

    Tadeusz Czachórski

  2. Department of Electrical and Electronic Engineering, Imperial College London, London, UK

    Erol Gelenbe

  3. Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland

    Krzysztof Grochla

  4. University of Houston, Houston, TX, USA

    Ricardo Lent

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Akinwande, O., Gelenbe, E. (2018). A Reinforcement Learning Approach to Adaptive Forwarding in Named Data Networking. In: Czachórski, T., Gelenbe, E., Grochla, K., Lent, R. (eds) Computer and Information Sciences. ISCIS 2018. Communications in Computer and Information Science, vol 935. Springer, Cham. https://doi.org/10.1007/978-3-030-00840-6_23

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  • DOI: https://doi.org/10.1007/978-3-030-00840-6_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00839-0

  • Online ISBN: 978-3-030-00840-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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