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Exploiting Knowledge for Better Mobility Support in the Future Internet

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Abstract

The ever-increasing mobile traffic calls for efficient mobility support at a global scale. Supporting “seamless” communication with network entities whose network location constantly changes, i.e., the mobility support problem, is extremely challenging for IP networking due to its host-centric communication model. Information-centric networking (ICN), as exemplified by the Named Data Networking (NDN) network architecture, offers new opportunities for mobility support. We identify a common design space for providing IP and NDN mobility support where solutions track the changing network locations of mobile network endpoints, and find that available design choices have been exhausted in this design space, leaving no room for substantial performance improvement. Recognizing this limitation, this paper proposes two novel knowledge-driven mobility support approaches to comprehensively improve mobility support performance. Such approaches exploit knowledge such as network topology and movement trajectory to tweak the network for better mobility support performance. A cross-architectural quantitative evaluation framework covering two communication scenarios and 5 quantifiable metrics is proposed to evaluate mobility support performance. Experiment results show that the knowledge-driven approaches significantly improve mobility support performance, demonstrating the potential of the knowledge-driven vision for providing better mobility support.

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Data Availability

The Rocketfuel [1] network topologies used in the experiments are available at https://research.cs.washington.edu/networking/rocketfuel.

Code Availability

The code for reproducing the results in this paper is available at https://github.com/KDN-Mobility.

Notes

  1. The network layer name to announce is determined by the forwarding mechanisms of a specific network architecture. For example, both IP and NDN use longest prefix matching when selecting routes, thus R should announce a prefix of ID.

References

  1. Spring N, Mahajan R, Wetherall D (2002) Measuring ISP topologies with Rocketfuel. ACM SIGCOMM Comput Commun Rev 32(4):133

    Article  Google Scholar 

  2. Qiu J, Du L, Zhang D, Su S, Tian Z (2019) Nei-TTE: intelligent traffic time estimation based on fine-grained time derivation of road segments for smart city. IEEE Trans Ind Inform 16(4): 2659

    Article  Google Scholar 

  3. Shafiq M, Tian Z, Bashir AK, Jolfaei A, Yu X (2020) Data mining and machine learning methods for sustainable smart cities traffic classification: A survey. Sustain Cities Soc 60:102177

    Article  Google Scholar 

  4. Shafiq M, Tian Z, Sun Y, Du X, Guizani M (2020) Selection of effective machine learning algorithm and Bot-IoT attacks traffic identification for internet of things in smart city. Futur Gener Comput Syst 107:433

    Article  Google Scholar 

  5. Tian Z, Gao X, Su S, Qiu J (2019) Vcash: a novel reputation framework for identifying denial of traffic service in internet of connected vehicles. IEEE Internet Things J 7(5):3901

    Article  Google Scholar 

  6. Tian Z, Gao X, Su S, Qiu J, Du X, Guizani M (2019) Evaluating reputation management schemes of internet of vehicles based on evolutionary game theory. IEEE Trans Veh Technol 68(6): 5971

    Article  Google Scholar 

  7. Zhang L, Afanasyev A, Burke J, Jacobson V, Claffy k, Crowley P, Papadopoulos C, Wang L, Zhang B (2014) Named data networking. ACM SIGCOMM Comput Commun Rev 44(3):66. https://doi.org/10.1145/2656877.2656887

    Article  Google Scholar 

  8. Xia Z, Zhang Y (2021) Towards knowledge-driven mobility support. In: Artificial intelligence for communications and networks: Second EAI International Conference, AICON 2020, Virtual Event, December 19-20, 2020, Proceedings 2. Springer International Publishing, pp 197–216

  9. Zhang Y, Afanasyev A, Burke J, Zhang L (2016) A survey of mobility support in named data networking. In: 2016 IEEE conference on computer communications workshops (INFOCOM WKSHPS). https://doi.org/10.1109/INFCOMW.2016.7562050, pp 83–88

  10. Perkins C, Bhagwat P (1994) A mobile networking system based on Internet protocol. IEEE Personal Commun 1(1):32. https://doi.org/10.1109/98.911984. Conference Name: IEEE Personal Communications

    Article  Google Scholar 

  11. Gao D, Rao Y, Foh CH, Zhang H, Vasilakos AV (2017) PMNDN: proxy based mobility support approach in mobile NDN environment. IEEE Trans Netw Serv Manag 14(1):191

    Article  Google Scholar 

  12. Azgin A, Ravindran R, Wang G (2014) A scalable mobility-centric architecture for named data networking. arXiv:1406.7049[cs]

  13. Lee J, Cho S, Kim D (2012) Device mobility management in content-centric networking. IEEE Commun Mag 50(12):28. https://doi.org/10.1109/MCOM.2012.6384448. Conference Name: IEEE Communications Magazine

    Article  Google Scholar 

  14. Hermans F, Ngai E, Gunningberg P (2012) Global source mobility in the content-centric networking architecture. In: Proceedings of the 1st ACM workshop on emerging name-oriented mobile networking design - architecture, algorithms, and applications (Association for Computing Machinery), NoM ’12. https://doi.org/10.1145/2248361.2248366, pp 13–18

  15. Kim Dh, Kim Jh, Kim Ys, Yoon Hs, Yeom I (2012) Mobility support in content centric networks. In: Proceedings of the second edition of the ICN workshop on Information-centric networking (Association for Computing Machinery), ICN ’12. https://doi.org/10.1145/2342488.2342492, pp 13–18

  16. Li D, CHuah MC (2013) SCOM: A scalable content centric network architecture with mobility support. In: 2013 IEEE 9th international conference on mobile ad-hoc and sensor networks. https://doi.org/10.1109/MSN.2013.44, pp 25–32

  17. Zhu Z, Zhang L, Wakikawa R (2020) Understanding apple’s back to my mac (BTMM) service. https://tools.ietf.org/html/rfc6281. Library Catalog: tools.ietf.org

  18. Afanasyev A, Yi C, Wang L, Zhang B, Zhang L (2015) SNAMP: Secure namespace mapping to scale NDN forwarding. In: 2015 IEEE conference on computer communications workshops (INFOCOM WKSHPS). https://doi.org/10.1109/INFCOMW.2015.7179398. ISSN: null, pp 281–286

  19. Rekhter Y, Li T (2020) A border gateway protocol 4 (BGP-4). https://tools.ietf.org/html/rfc1771. Library Catalog: tools.ietf.org

  20. Hu X, Li L, Mao ZM, Yang YR (2008) Wide-area IP network mobility. In: IEEE INFOCOM 2008 - The 27th conference on computer communications. https://doi.org/10.1109/INFOCOM.2008.148. ISSN: 0743-166X, pp 951–959

  21. Augé J., Carofiglio G, Grassi G, Muscariello L, Pau G, Zeng X (2018) MAP-Me: Managing anchor-less producer mobility in content-centric networks. IEEE Trans Netw Serv Manag 15 (2):596. https://doi.org/10.1109/TNSM.2018.2796720. Conference Name: IEEE Transactions on Network and Service Management

    Article  Google Scholar 

  22. Meddeb M, Dhraief A, Belghith A, Monteil T, Drira K, Gannouni S (2018) AFIRM: Adaptive forwarding based link recovery for mobility support in NDN/IoT networks. Futur Gener Comput Syst 87:351

    Article  Google Scholar 

  23. Zhang Y, Xia Z, Mastorakis S, Zhang L (2018) KITE: producer mobility support in named data networking. In: Proceedings of the 5th ACM conference on information-centric networking (Association for Computing Machinery), ICN ’18. https://doi.org/10.1145/3267955.3267959, pp 125–136

  24. Gao Z, Venkataramani A, Kurose J, Heimlicher S (2014) Towards a quantitative comparison of location-independent network architectures. In: Proceedings of the 2014 ACM conference on SIGCOMM (Association for Computing Machinery), SIGCOMM ’14. https://doi.org/10.1145/2619239.2626333, pp 259–270

  25. Chaganti V, Kurose J, Venkataramani A (2008) A cross-architectural quantitative evaluation of mobility approaches. In: IEEE INFOCOM 2018 - IEEE conference on computer communications. https://doi.org/10.1109/INFOCOM.2018.8485893, pp 639–647

  26. Kim H, Feamster N (2013) Improving network management with software defined networking. IEEE Commun Mag 51(2):114. https://doi.org/10.1109/MCOM.2013.6461195. Conference Name: IEEE Communications Magazine

    Article  Google Scholar 

  27. Mijumbi R, Serrat J, Gorricho JL, Bouten N, De Turck F, Boutaba R (2016) Network function virtualization: state-of-the-art and research challenges. IEEE Commun Surv Tutorials 18(1):236. https://doi.org/10.1109/COMST.2015.2477041. Conference Name: IEEE Communications Surveys Tutorials

    Article  Google Scholar 

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Acknowledgements

This work is supported by Peng Cheng Laboratory Funds (No. PCL2021A02). An earlier version of this work has been presented as a conference paper [8] in EAI AICON 2020, the conference proceedings of which can be found at the following SpringerLink: https://link.springer.com/book/10.1007%2F978-3-030-69066-3.

Funding

This work is supported by Peng Cheng Laboratory Funds (No. PCL2021A02).

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Authors and Affiliations

  1. Harbin Institute of Technology, Harbin, Heilongjiang, China

    Zhongda Xia, Yu Zhang & Binxing Fang

  2. Peng Cheng Laboratory, Shenzhen, Guangdong, China

    Yu Zhang & Binxing Fang

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  1. Zhongda Xia
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  2. Yu Zhang
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  3. Binxing Fang
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Correspondence to Yu Zhang.

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Xia, Z., Zhang, Y. & Fang, B. Exploiting Knowledge for Better Mobility Support in the Future Internet. Mobile Netw Appl 27, 1671–1687 (2022). https://doi.org/10.1007/s11036-021-01866-7

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