SDN/NFV Based Internet of Things for Multi-Tenant Networks

Authors

  • Sinh Do PhD Student, Department of Computer Science, National Chiao Tung University, Taiwan
  • Luong Vy Le College of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu, Taiwan
  • Bao Shuh Paul Lin Microelectronics & Information Research Center, National Chiao Tung University, Hsinchu, Taiwan
  • Li-Ping Tung Microelectronics & Information Research Center, National Chiao Tung University, Hsinchu, Taiwan

DOI:

https://doi.org/10.14738/tnc.66.5695

Keywords:

Software Defined Network (SDN), Software Defined Mobile Network (SDMN), Network Function Virtualization (NFV), Internet of Things (IoT), Wireless Sensor Network (WSN), P4, PSA(Portable Switch Architecture), ONOS.

Abstract

The Internet of Things (IoT) refers to variety of smart devices such as smartphones, tablets, and sensors that can interact and exchange of data among devices through the Internet. The diversity of IoT devices and their services have posed a larger range requirements of availability, throughput, latency, and performance in heterogeneous connectivity environments. Meanwhile, the existing networks often struggle with such of limitations in complex control protocols and difficulty in internetworking with billions of smart devices with different requirements such as latency and bandwidth allocations. These obstacles become substantial barriers to deploy services, as well as isolate between multiple co-existing tenants on the same physical network, deploy simultaneous protocols in the network, be stable to maintain the bandwidth and latency according to predefined QoS demands. These obstacles have recently been facilitated by Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies that enable the programming and monitoring in data plane. In this study, firstly, the authors investigate and propose a SDN/NFV based architecture for multi-tenant networks with plenty of network slices working in a shared physical infrastructure. Secondly, P4 and ONOS Controller are used to implement a deep programming in BMv2 devices to efficiently maintain the network motoring in order to guarantee the E2E latency of communicating channels. Finally, the VXLAN technologies are exploited to for network slicing with different purposes and applications, and Inband Network Telemetry (INT) is used to monitor network latency.

Author Biography

Sinh Do, PhD Student, Department of Computer Science, National Chiao Tung University, Taiwan

EECS, National Chiao Tung University, Taiwan.

Do Sinh ([email protected]) received the B.S. degree in electronics and telecommunication engineering from Da Nang University of Technology, Vietnam, in 1997. From 1997 to 2007, He worked for the Ministry of Post and Telecommunications, Vietnam. From 2007 to 2015, he was a lecturer in the Department of Information Technology, Dong A University, Da Nang, Vietnam. From 2003 to 2006, he also studied in the Department of Computer Science, Da Nang University of Technology. He received his M.Sc. in Computer Science in Sep 2006 Da Nang University of Technology, Vietnam. From 2015 to present, he is currently working toward his Ph.D. degree in the Department of Computer Science, National Chiao Tung University (NCTU), Taiwan. He is a researcher at SDN Technology Center, Broadband Mobile Lab, NCTU, Taiwan. His research interests include 5G network, SDN/NFV, Internet of Things, big data and machine learning.

References

(1) Open Networking Foundation, “SDN Architecture Overview,” Onf, no. 1, pp. 1–5, 2013.

(2) ETSI, “Network Functions Virtualisation (NFV); Architectural Framework,” ETSI GS NFV 002 v1.2.1, vol. 1, pp. 1–21, 2014.

(3) B. P. Lin, F. J. Lin, and L. Tung, “The Roles of 5G Mobile Broadband in the Development of IoT , Big Data , Cloud and SDN,” no. February, pp. 9–21, 2016.

(4) D. Sinh, L. Le, L. Tung, and B. P. Lin, “The Challenges of Applying SDN / NFV for 5G & IoT,” 14th IEEE – VTS Asia Pacific Wirel. Commun. Symp. (APWCS), Incheon, Korea, Aug 2017, pp. 138–142, 2017.

(5) L. Le, B. P. Lin, L. Tung, and D. Sinh, “SDN / NFV , Machine Learning , and Big Data Driven Network Slicing for 5G,” IEEE 1st 5G World Forum, Santa Clara, CA, July 9-11,2018

(6) D. Sinh, L. Le, B. P. Lin, and L. Tung, “SDN / NFV - A new approach of deploying network infrastructure for IoT,” 27th Wirel. Opt. Comminications Conf. (WOCC 2018), pp. 124–128, 2018.

(7) Z. L. K. Ben Pfaff, Bob Lantz, Brandon Heller, Casey Barker, Dan Cohn, Dan Talayco, David Erickson, Edward Crabbe, Glen Gibb, Guido Appenzeller, Jean Tourrilhes, Justin Pettit, KK Yap, Leon Poutievski, Martin Casado, Masahiko Takahashi, Masayoshi Kobayashi, Nick M, “OpenFlow Switch Specification,” Open Netw. Found., pp. 1–56, 2011.

(8) P. Bosshart, G. Varghese, D. Walker, D. Daly, G. Gibb, M. Izzard, N. McKeown, J. Rexford, C. Schlesinger, D. Talayco, and A. Vahdat, “P4: Programming Protocol-Independent Packet Processors,” ACM SIGCOMM Comput. Commun. Rev., vol. 44, no. 3, pp. 87–95, 2014.

(9) “P4 Brigade,” no. https://wiki.onosproject.org/display/ONOS/P4+brigade, p. 4.

(10) C. S. Architecture, “P4 16 Portable 1 Switch Architecture,” pp. 1–12, 2016.

(11) “Barefoot Networks. P4-bmv2. Website. https://github.com/p4lang/behavioral-model.,” p. 4.

(12) https://datatracker.ietf.org/doc/draft-ietf-nvo3-vxlan-gpe/?include_text=1, “vxlan-gpe-6.pdf.”

(13) Changhoon Kim, Parag Bhide, Ed Doe, Hugh Holbrook, Anoop Ghanwani, Dan Daly, Mukesh Hira, and Bruce Davie, “In-band Network Telemetry (INT),” no. September, pp. 1–28, 2015.

(14) “https://wiki.onosproject.org/display/ONOS/%28INT%29+In+Band+Network+Tele metry+with+ONOS+and+P4#id-(INT)InBandNetworkTelemetrywithONOSandP4- InstallBPFCollector,” p. 29.

(15) P. Berde, M. Gerola, J. Hart, Y. Higuchi, M. Kobayashi, T. Koide, and B. Lantz, “ONOS: towards an open, distributed SDN OS,” Proc. third Work. Hot Top. Softw. Defin. Netw. - HotSDN ’14, pp. 1–6, 2014.

(16) M. Ojo, D. Adami, and S. Giordano, “A SDN-IoT architecture with NFV implementation,” 2016 IEEE Globecom Work. GC Wkshps 2016 - Proc., 2016.

(17) F. Granelli, A. A. Gebremariam, M. Usman, F. Cugini, V. Stamati, M. Alitska, and P. Chatzimisios, “W IRELESS A CCESS IN F UTURE W IRELESS N ETWORKS : S CENARIOS AND S TANDARDS,”no. June, pp. 26–34, 2015.

(18) I. Stojmenovic, “Fog computing: A cloud to the ground support for smart things and machine-to- machine networks,” 2014 Australas. Telecommun. Networks Appl. Conf. ATNAC 2014, pp. 117–122, 2015.

(19) H. I. Kobo, A. M. Abu-mahfouz, and G. P. Hancke, “A Survey on Software-Defined Wireless Sensor Networks: Challenges and Design Requirements,” IEEE Commun. Surv. Tutorials, vol. 5, no. Submitted for publication, 2017.

(20) L. Velasco, L. Gifre, J.-L. Izquierdo-Zaragoza, F. Paolucci, A. P. Vela, A. Sgambelluri, M. Ruiz, and F. Cugini, “An Architecture to Support Autonomic Slice Networking,” J. Light. Technol., vol. 8724, no. c, pp. 1–1, 2017.

(21) J. Ordonez-Lucena, P. Ameigeiras, Di. Lopez, J. J. Ramos-Munoz, J. Lorca, and J. Folgueira, “Network Slicing for 5G with SDN/NFV: Concepts, Architectures, and Challenges,” IEEE Commun. Mag., vol. 55, no. 5, pp. 80–87, 2017.

(22) W. Miao, F. Agraz, S. Peng, S. Spadaro, G. Bernini, J. Perelló, G. Zervas, R. Nejabati, N. Ciulli, D. Simeonidou, H. Dorren, and N. Calabretta, “SDN-Enabled OPS With QoS Guarantee for Reconfigurable Virtual Data Center Networks,” vol. 7, no. 7, pp. 634–643, 2015.

(23) M. Gramaglia, I. Digon, V. Friderikos, D. Von Hugo, C. Mannweiler, and M. A. Puente, “Flexible Connectivity and QoE / QoS Management for 5G Networks : the 5G NORMA view.”

(24) S. S. Kumar, “Investigation of Security and QoS on SDN Firewall Using MAC Filtering,” pp. 0–4, 2017.

(25) N. Ul Hasan, W. Ejaz, I. Baig, M. Zghaibeh, and A. Anpalagan, “QoS-aware channel assignment for IoT-enabled smart building in 5G systems,” Int. Conf. Ubiquitous Futur. Networks, ICUFN, vol. 2016– Augus, pp. 924–928, 2016.

Downloads

Published

2019-01-01

How to Cite

Do, S., Le, L. V., Paul Lin, B. S., & Tung, L.-P. (2019). SDN/NFV Based Internet of Things for Multi-Tenant Networks. Discoveries in Agriculture and Food Sciences, 6(6), 40. https://doi.org/10.14738/tnc.66.5695