Skip to main content
SpringerLink
Log in

Service Function Chain Placement in Distributed Scenarios: A Systematic Review

  • Published:
Journal of Network and Systems Management Aims and scope Submit manuscript

Abstract

The network function virtualization (NFV) paradigm is an emerging technology that provides network flexibility by allowing the allocation of network functions over commodity hardware, like legacy servers in an IT infrastructure. In comparison with traditional network functions, implemented by dedicated hardware, the use of NFV reduces the operating and capital expenses and improves service deployment. In some scenarios, a complete network service can be composed of several functions, following a specific order, known as a service function chain (SFC). SFC placement is a complex task, already proved to be NP-hard. Moreover, in highly distributed scenarios, the network performance can also be impacted by other factors, such as traffic oscillations and high delays. Therefore, a given SFC placement strategy must be carefully developed to meet the network operator service constraints. In this paper, we present a systematic review of SFC placement advances in distributed scenarios. Differently from the current literature, we examine works over the last 10 years which addressed this problem while focusing on distributed scenarios. We then discuss the main scenarios where SFC placement has been deployed, as well as the several techniques used to create the placement strategies. We also present the main goals considered to create SFC placement strategies and highlight the metrics used to evaluate them.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. http://ieeexplore.ieee.org/Xplore/home.jsp.

  2. http://www.sciencedirect.com/.

  3. http://dl.acm.org/.

  4. https://kubernetes.io/.

  5. https://fiber.google.com/.

  6. https://osm.etsi.org/.

  7. https://wiki.openstack.org/wiki/Tacker,

  8. https://www.onap.org/.

References

  1. Asad, M., Basit, A., Qaisar, S., Ali, M.: Beyond 5g: Hybrid end-to-end quality of service provisioning in heterogeneous iot networks. IEEE Access 8, 192320–192338 (2020)

    Google Scholar 

  2. Sun, G., Li, Y., Liao, D., Chang, V.: Service function chain orchestration across multiple domains: a full mesh aggregation approach. IEEE Trans. Netw. Service Manag. 15(3), 1175–1191 (2018)

    Google Scholar 

  3. Sahhaf, S., Tavernier, W., Czentye, J., Sonkoly, B., Sköldström, P., Jocha, D., Garay, J.: Scalable architecture for service function chain orchestration. In: 2015 Fourth European Workshop on Software Defined Networks, pp. 19–24. IEEE (2015)

  4. Souza, R., Santos, M., Fernandes, S.: Importance measures for nfv data center: an availability evaluation. In: Anais do V Workshop Pré-IETF. SBC (2018)

  5. Sun, G., Chen, Z., Yu, H., Du, X., Guizani, M.: Online parallelized service function chain orchestration in data center networks. IEEE Access 7, 100147–100161 (2019)

    Google Scholar 

  6. Savi, M., Tornatore, M., Verticale, G.: Impact of processing-resource sharing on the placement of chained virtual network functions. IEEE Trans. Cloud Comput. (2019). https://doi.org/10.1109/TCC.2019.2914387

    Article  Google Scholar 

  7. Mijumbi, R., Serrat, J., Gorricho, J.L., Bouten, N., De Turck, F., Boutaba, R.: Network function virtualization: state-of-the-art and research challenges. IEEE Commun. Surv. Tutor. 18(1), 236–262 (2015)

    Google Scholar 

  8. Bonfim, M.S., Dias, K.L., Fernandes, S.F.: Integrated nfv/sdn architectures: a systematic literature review. ACM Comput. Surv. 51(6), 1–39 (2019)

    Google Scholar 

  9. Fan, J., Guan, C., Zhao, Y., Qiao, C.: Availability-aware mapping of service function chains. In: IEEE INFOCOM 2017-IEEE Conference on Computer Communications, pp. 1–9. IEEE (2017)

  10. Zhang, C., Wang, X., Dong, A., Zhao, Y., Li, F., Huang, M.: The intelligent multi-domain service function chain deployment: architecture, challenges and solutions. Int. J. Commun. Syst. 34, 1 (2021)

    Google Scholar 

  11. Barroso, L.A., Hölzle, U.: The datacenter as a computer: an introduction to the design of warehouse-scale machines. Synth. Lectures Comput. Architect. 4(1), 1–108 (2009)

    Google Scholar 

  12. Kuo, T.W., Liou, B.H., Lin, K.C.J., Tsai, M.J.: Deploying chains of virtual network functions: on the relation between link and server usage. IEEE/ACM Trans. Netw. 26(4), 1562–1576 (2018)

    Google Scholar 

  13. Nan, Y., Li, W., Bao, W., Delicato, F.C., Pires, P.F., Zomaya, A.Y.: Cost-effective processing for delay-sensitive applications in cloud of things systems. In: 2016 IEEE 15th international symposium on network computing and applications (NCA), pp. 162–169. IEEE (2016)

  14. Zhao, T., Zhou, S., Guo, X., Zhao, Y., Niu, Z.: A cooperative scheduling scheme of local cloud and internet cloud for delay-aware mobile cloud computing. In: 2015 IEEE Globecom Workshops (GC Wkshps), pp. 1–6. IEEE (2015)

  15. Chen, H., Wang, X., Zhao, Y., Song, T., Wang, Y., Xu, S., Li, L.: Mosc: a method to assign the outsourcing of service function chain across multiple clouds. Comput. Netw. 133, 166–182 (2018)

    Google Scholar 

  16. Liu, Y., Zhang, H., Chang, D., Hu, H.: Gdm: a general distributed method for cross-domain service function chain embedding. IEEE Trans. Netw. Service Manag. 17(3), 1446–1459 (2020)

    Google Scholar 

  17. Bhamare, D., Jain, R., Samaka, M., Erbad, A.: A survey on service function chaining. J. Netw. Comput. Appl. 75, 138–155 (2016)

    Google Scholar 

  18. Rotsos, C., King, D., Farshad, A., Bird, J., Fawcett, L., Georgalas, N., Gunkel, M., Shiomoto, K., Wang, A., Mauthe, A., et al.: Network service orchestration standardization: a technology survey. Comput. Standards Interfaces 54, 203–215 (2017)

    Google Scholar 

  19. Hantouti, H., Benamar, N., Taleb, T., Laghrissi, A.: Traffic steering for service function chaining. IEEE Commun. Surv. Tutor. 21(1), 487–507 (2018)

    Google Scholar 

  20. Souza, R., Dias, K., Fernandes, S.: Nfv data centers: a systematic review. IEEE Access 8, 51713–51735 (2020)

    Google Scholar 

  21. Schardong, F., Nunes, I., Schaeffer-Filho, A.: Nfv resource allocation: a systematic review and taxonomy of vnf forwarding graph embedding. Comput. Netw. 185, 107726 (2020)

    Google Scholar 

  22. Mirjalily, G., Zhiquan, L.: Optimal network function virtualization and service function chaining: a survey. Chin. J. Electron. 27(4), 704–717 (2018)

    Google Scholar 

  23. John, W., Pentikousis, K., Agapiou, G., Jacob, E., Kind, M., Manzalini, A., Risso, F., Staessens, D., Steinert, R., Meirosu, C.: Research directions in network service chaining. In: 2013 IEEE SDN for Future Networks and Services (SDN4FNS), pp. 1–7. IEEE (2013)

  24. Cardoso, J., Barros, A., May, N., Kylau, U.: Towards a unified service description language for the internet of services: requirements and first developments. In: 2010 IEEE International Conference on Services Computing, pp. 602–609. IEEE (2010)

  25. Sun, L., Dong, H., Ashraf, J.: Survey of service description languages and their issues in cloud computing. In: 2012 Eighth International Conference on Semantics, Knowledge and Grids, pp. 128–135. IEEE (2012)

  26. Ghazouani, S., Slimani, Y.: Towards a standardized cloud service description based on usdl. J. Syst. Softw. 132, 1–20 (2017)

    Google Scholar 

  27. Mehraghdam, S., Karl, H.: Placement of services with flexible structures specified by a yang data model. In: 2016 IEEE NetSoft Conference and Workshops (NetSoft), pp. 184–192. IEEE (2016)

  28. Katsaros, G., Menzel, M., Lenk, A., Revelant, J.R., Skipp, R., Eberhardt, J.: Cloud application portability with tosca, chef and openstack. In: 2014 IEEE International Conference on Cloud Engineering, pp. 295–302. IEEE (2014)

  29. Yang, S., Li, F., Trajanovski, S., Chen, X., Wang, Y., Fu, X.: Delay-aware virtual network function placement and routing in edge clouds. IEEE Trans. Mob. Comput. 99, 1 (2019)

    Google Scholar 

  30. Ren, W., Sun, Y., Luo, H., Obaidat, M.S.: A new scheme for iot service function chains orchestration in sdn-iot network systems. IEEE Syst. J. 13(4), 4081–4092 (2019)

    Google Scholar 

  31. Kouah, R., Alleg, A., Laraba, A., Ahmed, T.: Energy-aware placement for iot-service function chain. In: 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), pp. 1–7. IEEE (2018)

  32. Kiji, N., Sato, T., Shinkuma, R., Oki, E.: Virtual network function placement and routing for multicast service chaining using merged paths. Opt. Switch. Netw. 36, 100554 (2020)

    Google Scholar 

  33. Jiao, S., Zhang, X., Yu, S., Song, X., Xu, Z.: Joint virtual network function selection and traffic steering in telecom networks. In: GLOBECOM 2017-2017 IEEE Global Communications Conference, pp. 1–7. IEEE (2017)

  34. Alameddine, H.A., Assi, C., Tushar, M.H.K., Yu, J.Y.: Low-latency service schedule orchestration in nfv-based networks. In: 2019 IEEE Conference on Network Softwarization (NetSoft), pp. 378–386. IEEE (2019)

  35. Riera, J.F., Escalona, E., Batalle, J., Grasa, E., Garcia-Espin, J.A.: Virtual network function scheduling: concept and challenges. In: 2014 International Conference on Smart Communications in Network Technologies (SaCoNeT), pp. 1–5. IEEE (2014)

  36. Mijumbi, R., Serrat, J., Gorricho, J.L., Bouten, N., De Turck, F., Davy, S.: Design and evaluation of algorithms for mapping and scheduling of virtual network functions. In: Proceedings of the 2015 1st IEEE conference on network softwarization (NetSoft), pp. 1–9. IEEE (2015)

  37. Qu, L., Assi, C., Shaban, K.: Delay-aware scheduling and resource optimization with network function virtualization. IEEE Trans. Commun. 64(9), 3746–3758 (2016)

    Google Scholar 

  38. Coutinho, E.F., de Carvalho Sousa, F.R., Rego, P.A.L., Gomes, D.G., de Souza, J.N.: Elasticity in cloud computing: a survey. Ann. Telecommun. 70(7–8), 289–309 (2015)

    Google Scholar 

  39. Fulber-Garcia, V., Duarte, E.P., Jr., Huff, A., dos Santos, C.R.: Network service topology: Formalization, taxonomy and the custom specification model. Comput. Netw. 178, 107337 (2020)

    Google Scholar 

  40. Jin, H., Zhu, X., Zhao, C.: Computation offloading optimization based on probabilistic sfc for mobile online gaming in heterogeneous network. IEEE Access 7, 52168–52180 (2019)

    Google Scholar 

  41. Pei, J., Hong, P., Xue, K., Li, D.: Efficiently embedding service function chains with dynamic virtual network function placement in geo-distributed cloud system. IEEE Trans. Parallel Distrib. Syst. 30(10), 2179–2192 (2018)

    Google Scholar 

  42. Bouet, M., Leguay, J., Combe, T., Conan, V.: Cost-based placement of vdpi functions in nfv infrastructures. Int. J. Netw. Manag. 25(6), 490–506 (2015)

    Google Scholar 

  43. Bari, F., Chowdhury, S.R., Ahmed, R., Boutaba, R., Duarte, O.C.M.B.: Orchestrating virtualized network functions. IEEE Trans. Netw. Service Manag. 13(4), 725–739 (2016)

    Google Scholar 

  44. Liu, Y., Pei, J., Hong, P., Li, D.: Cost-efficient virtual network function placement and traffic steering. In: ICC 2019-2019 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2019)

  45. Noghani, K.A., Kassler, A., Taheri, J.: On the cost-optimality trade-off for service function chain reconfiguration. In: 2019 IEEE 8th International Conference on Cloud Networking (CloudNet), pp. 1–6. IEEE (2019)

  46. Feng, H., Llorca, J., Tulino, A.M., Molisch, A.F.: Optimal dynamic cloud network control. IEEE/ACM Trans. Netw. 26(5), 2118–2131 (2018)

    Google Scholar 

  47. He, W., Li, W., Xu, S.: A lyapunov drift-plus-penalty-based multi-objective optimization of energy consumption, construction period and benefit. KSCE J. Civ. Eng. 146, 1–14 (2020)

    Google Scholar 

  48. Neely, M.J.: Queue stability and probability 1 convergence via lyapunov optimization. arXiv preprint arXiv:1008.3519 (2010)

  49. Tang, L., Yang, H., Ma, R., Hu, L., Wang, W., Chen, Q.: Queue-aware dynamic placement of virtual network functions in 5g access network. IEEE Access 6, 44291–44305 (2018)

    Google Scholar 

  50. Gupta, L., Samaka, M., Jain, R., Erbad, A., Bhamare, D., Metz, C.: Colap: A predictive framework for service function chain placement in a multi-cloud environment. In: 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), pp. 1–9. IEEE (2017)

  51. Yao, Y., Guo, S., Li, P., Liu, G., Zeng, Y.: Forecasting assisted vnf scaling in nfv-enabled networks. Computer Networks 168, 107040 (2020)

    Google Scholar 

  52. Jahromi, N.T., Kianpisheh, S., Glitho, R.H.: Online vnf placement and chaining for value-added services in content delivery networks. In: 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), pp. 19–24. IEEE (2018)

  53. Hejja, K., Hesselbach, X.: Offline and online power aware resource allocation algorithms with migration and delay constraints. Comput. Netw. 158, 17–34 (2019)

    Google Scholar 

  54. Mohamad, A., Hassanein, H.S.: On demonstrating the gain of sfc placement with vnf sharing at the edge. In: 2019 IEEE Global Communications Conference (GLOBECOM), pp. 1–6. IEEE (2019)

  55. Gurobi Optimization, I.: Gurobi optimizer reference manual. http://www.gurobi.com (2018)

  56. Guo, H., Wang, Y., Li, Z., Qiu, X., An, H., Yuan, N., et al.: Cost-aware placement and chaining of service function chain with vnf instance sharing. In: NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium, pp. 1–8. IEEE (2020)

  57. Luo, Z., Wu, C., Li, Z., Zhou, W.: Scaling geo-distributed network function chains: a prediction and learning framework. IEEE J. Select. Areas Commun. 37(8), 1838–1850 (2019)

    Google Scholar 

  58. Guo, S., Dai, Y., Xu, S., Qiu, X., Qi, F.: Trusted cloud-edge network resource management: Drl-driven service function chain orchestration for iot. IEEE Internet Things J. 7, 7 (2019)

    Google Scholar 

  59. Nguyen, D.T., Pham, C., Nguyen, K.K., Cheriet, M.: Placement and chaining for run-time iot service deployment in edge-cloud. IEEE Trans. Netw. Service Manag. 17(1), 459–472 (2019)

    Google Scholar 

  60. Fang, L., Zhang, X., Sood, K., Wang, Y., Yu, S.: Reliability-aware virtual network function placement in carrier networks. J. Netw. Comput. Appl. 154, 102536 (2020)

    Google Scholar 

  61. Tomassilli, A., Giroire, F., Huin, N., Pérennes, S.: Provably efficient algorithms for placement of service function chains with ordering constraints. In: IEEE INFOCOM 2018-IEEE Conference on Computer Communications, pp. 774–782. IEEE (2018)

  62. Tastevin, N., Obadia, M., Bouet, M.: A graph approach to placement of service functions chains. In: 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), pp. 134–141. IEEE (2017)

  63. Chamberland, S., St-Hilaire, M., Pierre, S.: On the point-of-presence optimization problem in ip networks. Can. J. Electr. Comput. Eng. 30(3), 137–143 (2005)

    Google Scholar 

  64. Chamberland, S.: Point of presence design in internet protocol networks with performance guarantees. Comput. Oper. Res. 32(12), 3247–3264 (2005)

    MATH  Google Scholar 

  65. Tashtarian, F., Zhani, M.F., Fatemipour, B., Yazdani, D.: Codec: a cost-effective and delay-aware sfc deployment. IEEE Trans. Netw. Service Manag. 17, 793 (2019)

    Google Scholar 

  66. Alleg, A., Ahmed, T., Mosbah, M., Riggio, R., Boutaba, R.: Delay-aware vnf placement and chaining based on a flexible resource allocation approach. In: 2017 13th International Conference on Network and Service Management (CNSM), pp. 1–7. IEEE (2017)

  67. Cai, J., Huang, Z., Luo, J., Liu, Y., Zhao, H., Liao, L.: Composing and deploying parallelized service function chains. J. Netw. Comput. Appl. 163, 102637 (2020)

    Google Scholar 

  68. Luizelli, M.C., Bays, L.R., Buriol, L.S., Barcellos, M.P., Gaspary, L.P.: 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. IEEE (2015)

  69. Sheoran, A., Sharma, P., Fahmy, S., Saxena, V.: Contain-ed: an nfv micro-service system for containing e2e latency. ACM SIGCOMM Comput. Commun. Rev. 47(5), 54–60 (2017)

    Google Scholar 

  70. Xu, Q., Gao, D., Li, T., Zhang, H.: Low latency security function chain embedding across multiple domains. IEEE Access 6, 14474–14484 (2018)

    Google Scholar 

  71. Martín-Pérez, J., Bernardos, C.J.: Multi-domain vnf mapping algorithms. In: 2018 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), pp. 1–6. IEEE (2018)

  72. Zamani, A., Sharifian, S.: A novel approach for service function chain (sfc) mapping with multiple sfc instances in a fog-to-cloud computing system. In: 2018 4th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS), pp. 48–52. IEEE (2018)

  73. Subramanya, T., Harutyunyan, D., Riggio, R.: Machine learning-driven service function chain placement and scaling in mec-enabled 5g networks. Comput. Netw. 166, 106980 (2020)

    Google Scholar 

  74. Bhamare, D., Samaka, M., Erbad, A., Jain, R., Gupta, L., Chan, H.A.: Optimal virtual network function placement in multi-cloud service function chaining architecture. Comput. Commun. 102, 1–16 (2017)

    Google Scholar 

  75. Bhamare, D., Erbad, A., Jain, R., Zolanvari, M., Samaka, M.: Efficient virtual network function placement strategies for cloud radio access networks. Comput. Commun. 127, 50–60 (2018)

    Google Scholar 

  76. Forney, G.D.: The viterbi algorithm. Proc. IEEE 61(3), 268–278 (1973)

    MathSciNet  Google Scholar 

  77. Sun, G., Li, Y., Li, Y., Liao, D., Chang, V.: Low-latency orchestration for workflow-oriented service function chain in edge computing. Future Gen. Comput. Syst. 85, 116–128 (2018)

    Google Scholar 

  78. Santos, J., Wauters, T., Volckaert, B., De Turck, F.: Towards delay-aware container-based service function chaining in fog computing. In: NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium, pp. 1–9. IEEE (2020)

  79. Xu, Y., Kafle, V.P.: A mathematical model and dynamic programming based scheme for service function chain placement in nfv. IEICE Trans. Inform. Syst. 102(5), 942–951 (2019)

    Google Scholar 

  80. Li, D., Hong, P., Xue, K., Pei, J.: Virtual network function placement and resource optimization in nfv and edge computing enabled networks. Comput. Netw. 152, 12–24 (2019)

    Google Scholar 

  81. Shang, X., Li, Z., Yang, Y.: Placement of highly available virtual network functions through local rerouting. In: 2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), pp. 80–88. IEEE (2018)

  82. Khebbache, S., Hadji, M., Zeghlache, D.: Virtualized network functions chaining and routing algorithms. Comput. Netw. 114, 95–110 (2017)

    Google Scholar 

  83. Carpio, F., Bziuk, W., Jukan, A.: Replication of virtual network functions: optimizing link utilization and resource costs. In: 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 521–526. IEEE (2017)

  84. Li, G., Feng, B., Zhou, H., Zhang, Y., Sood, K., Yu, S.: Adaptive service function chaining mappings in 5g using deep q-learning. Comput. Commun. 152, 305–315 (2020)

    Google Scholar 

  85. Song, X., Zhang, X., Yu, S., Jiao, S., Xu, Z.: Resource-efficient virtual network function placement in operator networks. In: GLOBECOM 2017-2017 IEEE Global Communications Conference, pp. 1–7. IEEE (2017)

  86. Soualah, O., Mechtri, M., Ghribi, C., Zeghlache, D.: Energy efficient algorithm for vnf placement and chaining. In: 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), pp. 579–588. IEEE (2017)

  87. ISG, N.: Network functions virtualisation (nfv)-virtualisation requirements. ETSI Technical Report (2013)

  88. Sun, G., Li, Y., Yu, H., Vasilakos, A.V., Du, X., Guizani, M.: Energy-efficient and traffic-aware service function chaining orchestration in multi-domain networks. Future Gen. Comput. Syst. 91, 347–360 (2019)

    Google Scholar 

  89. Xu, Z., Zhang, X., Yu, S., Zhang, J.: Energy-efficient virtual network function placement in telecom networks. In: 2018 IEEE International Conference on Communications (ICC), pp. 1–7. IEEE (2018)

  90. Zhang, X., Xu, Z., Fan, L., Yu, S., Qu, Y.: Near-optimal energy-efficient algorithm for virtual network function placement. IEEE Trans. Cloud Comput. 99, 1–1 (2019)

    Google Scholar 

  91. Saha, S., Sarkar, J., Dwivedi, A., Dwivedi, N., Narasimhamurthy, A.M., Roy, R.: A novel revenue optimization model to address the operation and maintenance cost of a data center. J. Cloud Comput. 5(1), 1–23 (2016)

    Google Scholar 

  92. Sheikholeslami, F., Navimipour, N.J.: Service allocation in the cloud environments using multi-objective particle swarm optimization algorithm based on crowding distance. Swarm Evol. Comput. 35, 53–64 (2017)

    Google Scholar 

  93. Badshah, A., Ghani, A., Shamshirband, S., Chronopoulos, A.T.: Optimising infrastructure as a service provider revenue through customer satisfaction and efficient resource provisioning in cloud computing. IET Commun. 13(18), 2913–2922 (2019)

    Google Scholar 

  94. Badshah, A., Ghani, A., Shamshirband, S., Aceto, G., Pescapè, A.: Performance-based service-level agreement in cloud computing to optimise penalties and revenue. IET Commun. 14(7), 1102–1112 (2020)

    Google Scholar 

  95. Mechtri, M., Ghribi, C., Soualah, O., Zeghlache, D.: Nfv orchestration framework addressing sfc challenges. IEEE Commun. Mag. 55(6), 16–23 (2017)

    Google Scholar 

  96. Ma, Y., Liang, W., Xu, Z., Guo, S.: Profit maximization for admitting requests with network function services in distributed clouds. IEEE Trans. Parallel Distrib. Syst. 30(5), 1143–1157 (2018)

    Google Scholar 

  97. Xie, Y., Wang, S., Dai, Y.: Revenue-maximizing virtualized network function chain placement in dynamic environment. Future Gen. Comput. Syst. (2020). https://doi.org/10.1016/j.future.2020.03.011

    Article  Google Scholar 

  98. Li, G., Zhou, H., Feng, B., Zhang, Y., Yu, S.: Efficient provision of service function chains in overlay networks using reinforcement learning. IEEE Trans. Cloud Comput. (2019). https://doi.org/10.1109/TCC.2019.2961093

    Article  Google Scholar 

  99. Li, G., Zhou, H., Feng, B., Li, G.: Context-aware service function chaining and its cost-effective orchestration in multi-domain networks. IEEE Access 6, 34976–34991 (2018)

    Google Scholar 

  100. Cappanera, P., Paganelli, F., Paradiso, F.: Vnf placement for service chaining in a distributed cloud environment with multiple stakeholders. Comput. Commun. 133, 24–40 (2019)

    Google Scholar 

  101. Chen, Y.T., Liao, W.: Mobility-aware service function chaining in 5g wireless networks with mobile edge computing. In: ICC 2019-2019 IEEE International Conference on Communications (ICC), pp. 1–6. IEEE (2019)

  102. Cui, Y., Geng, Z., Zhu, Q., Han, Y.: Multi-objective optimization methods and application in energy saving. Energy 125, 681–704 (2017)

    Google Scholar 

  103. Bouten, N., Mijumbi, R., Serrat, J., Famaey, J., Latré, S., De Turck, F.: Semantically enhanced mapping algorithm for affinity-constrained service function chain requests. IEEE Trans. Netw. Service Manag. 14(2), 317–331 (2017)

    Google Scholar 

  104. Gupta, L., Jain, R., Erbad, A., Bhamare, D.: The p-art framework for placement of virtual network services in a multi-cloud environment. Comput. Commun. 139, 103–122 (2019)

    Google Scholar 

  105. Zhang, C., Wang, X., Dong, A., Zhao, Y., He, Q., Huang, M.: Energy efficient network service deployment across multiple sdn domains. Comput. Commun. 151, 449–462 (2020)

    Google Scholar 

  106. Troia, S., Cibari, A., Alvizu, R., Maier, G.: Dynamic programming of network slices in software-defined metro-core optical networks. Opt. Switch. Netw. 36, 100551 (2020)

    Google Scholar 

  107. Harutyunyan, D., Fedrizzi, R., Shahriar, N., Boutaba, R., Riggio, R.: Orchestrating end-to-end slices in 5g networks. In: 2019 15th International Conference on Network and Service Management (CNSM), pp. 1–9. IEEE (2019)

  108. Harutyunyan, D., Shahriar, N., Boutaba, R., Riggio, R.: Latency-aware service function chain placement in 5g mobile networks. In: 2019 IEEE Conference on Network Softwarization (NetSoft), pp. 133–141. IEEE (2019)

  109. Jin, H., Jin, Y., Lu, H., Zhao, C., Peng, M.: Nfv and sfc: a case study of optimization for virtual mobility management. IEEE J. Select. Areas Commun. 36(10), 2318–2332 (2018)

    Google Scholar 

  110. Shang, X., Liu, Z., Yang, Y.: Network congestion-aware online service function chain placement and load balancing. In: Proceedings of the 48th International Conference on Parallel Processing, pp. 1–10 (2019)

  111. Eramo, V., Miucci, E., Ammar, M., Lavacca, F.G.: An approach for service function chain routing and virtual function network instance migration in network function virtualization architectures. IEEE/ACM Trans. Network. 25(4), 2008–2025 (2017)

    Google Scholar 

  112. Siasi, N., Jaesim, A., Ghani, N.: Tabu search for efficient service function chain provisioning in fog networks. In: 2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC), pp. 145–150. IEEE (2019)

  113. Tajiki, M.M., Shojafar, M., Akbari, B., Salsano, S., Conti, M., Singhal, M.: Joint failure recovery, fault prevention, and energy-efficient resource management for real-time sfc in fog-supported sdn. Comput. Netw. 162, 106850 (2019)

    Google Scholar 

  114. Son, J., Buyya, R.: Latency-aware virtualized network function provisioning for distributed edge clouds. J. Syst. Softw. 152, 24–31 (2019)

    Google Scholar 

  115. Zhao, D., Sun, G., Liao, D., Xu, S., Chang, V.: Mobile-aware service function chain migration in cloud-fog computing. Future Gen. Comput. Syst. 96, 591–604 (2019)

    Google Scholar 

  116. Chiosi, M., BT, C.D., Peter, W., Centurylink, A.R., James, F., Michael, B., Waqar, K., Michael, F.: Network functions virtualization—introductory white paper issue 1 network functions virtualization an introduction, benefits, enablers, challenges & call for action contributing organisations & authors (2012)

  117. Condoluci, M., Mahmoodi, T.: Softwarization and virtualization in 5g mobile networks: benefits, trends and challenges. Comput. Netw. 146, 65–84 (2018)

    Google Scholar 

  118. Stiawan, D.: Personal data protection and liability of internet service provider a comparative. Int. J. Electr. Comput. Eng. 9(4), 3175–3184 (2019)

    Google Scholar 

  119. Hong, D.K., Ma, Y., Banerjee, S., Mao, Z.M.: Incremental deployment of sdn in hybrid enterprise and isp networks. In: Proceedings of the Symposium on SDN Research, pp. 1–7 (2016)

  120. Yu, H., Lee, H., Jeon, H.: What is 5g? Emerging 5g mobile services and network requirements. Sustainability 9(10), 1848 (2017)

    Google Scholar 

  121. LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)

    Google Scholar 

  122. Sutton, R.S., Barto, A.G.: Reinforcement learning: an introduction. MIT, New York (2018)

    MATH  Google Scholar 

  123. Harkous, H., Jarschel, M., He, M., Priest, R., Kellerer, W.: Towards understanding the performance of p4 programmable hardware. In: 2019 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS), pp. 1–6. IEEE (2019)

  124. Consortium, P.L.: P4 language and related specifications. https://p4.org/specs/ (2021)

Download references

Author information

Authors and Affiliations

  1. Universidade Federal de Pernambuco, Recife, Brazil

    Guto Leoni Santos, Diego de Freitas Bezerra, Élisson da Silva Rocha, Leylane Ferreira, André Luis Cavalcanti Moreira, Judith Kelner & Djamel Sadok

  2. Universidade Federal do Pará, Belém, Brazil

    Glauco Estácio Gonçalves

  3. Ericsson Research, Indaiatuba, Brazil

    Maria Valéria Marquezini

  4. Eötvös Loránd University, Budapest, Hungary

    Ákos Recse

  5. Ericsson Research, Kista, Sweden

    Amardeep Mehta

  6. Universidade de Pernambuco, Recife, Brazil

    Patricia Takako Endo

Authors
  1. Guto Leoni Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diego de Freitas Bezerra
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Élisson da Silva Rocha
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Leylane Ferreira
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. André Luis Cavalcanti Moreira
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Glauco Estácio Gonçalves
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Maria Valéria Marquezini
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ákos Recse
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Amardeep Mehta
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Judith Kelner
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Djamel Sadok
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Patricia Takako Endo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Patricia Takako Endo.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Santos, G.L., Bezerra, D.d.F., Rocha, É.d.S. et al. Service Function Chain Placement in Distributed Scenarios: A Systematic Review. J Netw Syst Manage 30, 4 (2022). https://doi.org/10.1007/s10922-021-09626-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10922-021-09626-4

Keywords

Search

Navigation