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Efficient algorithms to minimize the end-to-end latency of edge network function virtualization

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Abstract

In future wireless networks, network function virtualization will lay the foundation for establishing a new dynamic resource management framework to efficiently utilize network resources. The main problem discussed in this paper is the minimization of total latency for an edge network and how to solve it efficiently. A model of users, virtual network functions and hosting devices has been taken, and is used to find the minimum latency using integer linear programming. The problem is NP-hard and takes exponential time to return the optimal solution. We apply the stable matching based algorithm to solve the problem in polynomial time and then utilize local search to improve its efficiency further. From extensive performance evaluation, it is found that our proposed algorithm is very close to the optimal scheme in terms of latency and better in terms of time complexity.

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References

  • Andrews JG, Buzzi S, Choi W, Hanly SV, Lozano A, Soong ACK, Zhang JC (2014) What will 5g be? IEEE J Select Areas Commun 32(6):1065–1082. https://doi.org/10.1109/JSAC.2014.2328098

    Article  Google Scholar 

  • Baran P (1964) On distributed communications networks. IEEE Trans Commun Syst 12(1):1–9. https://doi.org/10.1109/TCOM.1964.1088883

    Article  Google Scholar 

  • Bouras C, Kollia A, Papazois A (2017) Sdn nfv in 5g: Advancements and challenges. In: 2017 20th Conference on innovations in clouds, internet and networks (ICIN), pp 107–111. https://doi.org/10.1109/ICIN.2017.7899398

  • Campioni F, Choudhury S, Al-Turjman F (2019) Scheduling rfid networks in the iot and smart health era. J Ambient Intell Hum Comput:1–15

  • Chiosi M, Clarke D, Willis Cablelabs P, Donley C, Johnson Centurylink L, Bugenhagen M, Feger J, Khan W, China C, Cui H, Chen China Deng C,   T, Baohua L, Zhenqiang S, Wright S (2013) Network functions virtualisation (nfv) network operator perspectives on industry progress https://doi.org/10.13140/RG.2.1.4110.2883

  • Cho D, Taheri J, Zomaya AY, Wang L (2017) Virtual network function placement: Towards minimizing network latency and lead time. In: 2017 IEEE International conference on cloud computing technology and science (CloudCom), pp 90–97. https://doi.org/10.1109/CloudCom.2017.12

  • Chu W (2018) NFV and NFV-based security services, vol 15. Wiley, Oxford, pp 347–372. https://doi.org/10.1002/9781119293071.ch15

    Book  Google Scholar 

  • Chu Q, Cui L, Zhang Y (2017) Joint computing and storage resource allocation based on stable matching in data centers. In: 2017 ieee 3rd international conference on big data security on cloud (bigdatasecurity), ieee international conference on high performance and smart computing (hpsc), and ieee international conference on intelligent data and security (ids), pp 207–212. https://doi.org/10.1109/BigDataSecurity.2017.36

  • Cisco (2017) Cisco visual networking index: global mobile data traffic forecast update, 2017–2022. Cisco White Paper

  • Cziva R, Pezaros DP (2017a) Container network functions: bringing nfv to the network edge. IEEE Commun Mag 55(6):24–31. https://doi.org/10.1109/MCOM.2017.1601039

    Article  Google Scholar 

  • Cziva R, Pezaros DP (2017b) On the latency benefits of edge nfv. In: 2017 ACM/IEEE symposium on architectures for networking and communications systems (ANCS), pp 105–106. https://doi.org/10.1109/ANCS.2017.23

  • Cziva R, Anagnostopoulos C, Pezaros D (2018) Dynamic, latency-optimal vnf placement at the network edge, pp 693–701. https://doi.org/10.1109/INFOCOM.2018.8486021

  • Dawande M, Kalagnanam J, Keskinocak P, Salman F, Ravi R (2000) Approximation algorithms for the multiple knapsack problem with assignment restrictions. J Comb Optim 4(2):171–186. https://doi.org/10.1023/A:1009894503716

    Article  MathSciNet  MATH  Google Scholar 

  • Dengiz B, Altiparmak F, Smith AE (1997) Local search genetic algorithm for optimal design of reliable networks. IEEE Trans Evol Comput 1(3):179–188. https://doi.org/10.1109/4235.661548

    Article  Google Scholar 

  • Gale D, Shapley LS (1962) College admissions and the stability of marriage. Am Math Mon 69(1):9–15. http://www.jstor.org/stable/2312726

  • Ghai KS, Choudhury S, Yassine A (2019) A stable matching based algorithm to minimize the end-to-end latency of edge nfv. Proced Comput Sci 151:377–384

    Article  Google Scholar 

  • Hassan MY, Hussain F, Hossen MS, Choudhury S, Alam MM (2017a) A near optimal interference minimization resource allocation algorithm for d2d communication. In: 2017 IEEE international conference on communications (ICC), IEEE, pp 1–6

  • Hassan Y, Hussain F, Hossen S, Choudhury S, Alam MM (2017b) Interference minimization in d2d communication underlaying cellular networks. IEEE Access 5:22471–22484

    Article  Google Scholar 

  • Hossen MS, Hassan MY, Hussain F, Choudhury S, Alam MM (2018) Relax online resource allocation algorithms for d2d communication. Int J Commun Syst 31(10):e3555

    Article  Google Scholar 

  • Hu F, Qiu M, Li J, Grant T, Tylor D, McCaleb S, Butler L, Hamner R (2011) A review on cloud computing: design challenges in architecture and security. CIT 19:25–55

    Article  Google Scholar 

  • Irving RW, Leather P, Gusfield D (1987) An efficient algorithm for the“optimal” stable marriage. J ACM 34(3):532–543. https://doi.org/10.1145/28869.28871

    Article  Google Scholar 

  • Islam MT, Taha AEM, Akl S, Choudhury S (2015) A local search algorithm for resource allocation for underlaying device-to-device communications. In: 2015 IEEE global communications conference (GLOBECOM), IEEE, pp 1–6

  • Kim S, Lee I (2018) Iot device security based on proxy re-encryption. J Ambient Intell Hum Comput 9(4):1267–1273. https://doi.org/10.1007/s12652-017-0602-5

    Article  MathSciNet  Google Scholar 

  • Luizelli MC, Bays LR, Buriol LS, Barcellos MP, Gaspary LP (2015) Piecing together the nfv provisioning puzzle: efficient placement and chaining of virtual network functions. In: 2015 IFIP/IEEE international symposium on integrated network management (IM), pp 98–106. https://doi.org/10.1109/INM.2015.7140281

  • McVitie DG, Wilson LB (1971) Three procedures for the stable marriage problem. Commun ACM 14(7):491–492. https://doi.org/10.1145/362619.362632

    Article  Google Scholar 

  • Moens H, Turck FD (2014) Vnf-p: A model for efficient placement of virtualized network functions. In: 10th International conference on network and service management (CNSM) and workshop, pp 418–423. https://doi.org/10.1109/CNSM.2014.7014205

  • Munir A, Laskar MTR, Hossen MS, Choudhury S (2019) A localized fault tolerant load balancing algorithm for rfid systems. J Ambient Intell Hum Comput 10(11):4305–4317

    Article  Google Scholar 

  • Pandi S, Wunderlich S, Fitzek FHP (2018) Reliable low latency wireless mesh networks —from myth to reality. In: 2018 15th IEEE annual consumer communications networking conference (CCNC), pp 1–2. https://doi.org/10.1109/CCNC.2018.8319326

  • Park JH, Yen NY (2018) Advanced algorithms and applications based on iot for the smart devices. J Ambient Intell Hum Comput 9(4):1085–1087. https://doi.org/10.1007/s12652-018-0715-5

    Article  Google Scholar 

  • Satyanarayanan M (2017) The emergence of edge computing. Computer 50(1):30–39. https://doi.org/10.1109/MC.2017.9

    Article  Google Scholar 

  • Shi W, Dustdar S (2016) The promise of edge computing. Computer 49(5):78–81. https://doi.org/10.1109/MC.2016.145

    Article  Google Scholar 

  • Shi W, Cao J, Zhang Q, Li Y, Xu L (2016) Edge computing: vision and challenges. IEEE IoT J 3(5):637–646. https://doi.org/10.1109/JIOT.2016.2579198

    Article  Google Scholar 

  • Sugimoto S, Hattori T, Izumi T, Kawano H (2009) Fast kansei matching method as an algorithm for the solution of extended stable marriage problem. In: 2009 International conference on biometrics and kansei engineering, pp 209–214. https://doi.org/10.1109/ICBAKE.2009.55

  • Tahmasbi Nejad MA, Parsaeefard S, Maddah-Ali MA, Mahmoodi T, Khalaj BH (2018) vspace: Vnf simultaneous placement, admission control and embedding. IEEE J Select Areas Commun 36(3):542–557. https://doi.org/10.1109/JSAC.2018.2815318

    Article  Google Scholar 

  • Tashtarian F, Varasteh A, Montazerolghaem A, Kellerer W (2017) Distributed vnf scaling in large-scale datacenters: an admm-based approach. In: 2017 IEEE 17th international conference on communication technology (ICCT), pp 471–480. https://doi.org/10.1109/ICCT.2017.8359682

  • Wang S, Hou Y, Gao F, Ji X (2016) A novel iot access architecture for vehicle monitoring system. In: 2016 IEEE 3rd world forum on internet of things (WF-IoT), pp 639–642. https://doi.org/10.1109/WF-IoT.2016.7845396

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Authors and Affiliations

  1. Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada

    Karanbir Singh Ghai & Salimur Choudhury

  2. Department of Software Engineering, Lakehead University, Thunder Bay, ON, Canada

    Abdulsalam Yassine

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  1. Karanbir Singh Ghai
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  2. Salimur Choudhury
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  3. Abdulsalam Yassine
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Correspondence to Karanbir Singh Ghai.

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Ghai, K.S., Choudhury, S. & Yassine, A. Efficient algorithms to minimize the end-to-end latency of edge network function virtualization. J Ambient Intell Human Comput 11, 3963–3974 (2020). https://doi.org/10.1007/s12652-019-01630-6

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