The Downside of Software-Defined Networking in Wireless Network

Authors

  • Zahraa Zakariya Saleh Department of English, College of Education and Language, Lebanese French University, Erbil 44001, Kurdistan Region, Iraq. http://orcid.org/0000-0002-9547-5329
  • Qahhar Muhammad Qadir Department of Electrical Engineering, College of Engineering, Salahaddin University - Erbil, Erbil 44001, Kurdistan Region, Iraq. and Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewler, Erbil 44001, Kurdistan Region, Iraq. http://orcid.org/0000-0002-5702-8712

DOI:

https://doi.org/10.25079/ukhjse.v4n2y2020.pp147-156

Keywords:

SDN, Software Defined Network, CSMA, WSN, IoT

Abstract

Mobile traffic volumes have grown exponentially because of the increase in services and applications. Traditional networks are complex to manage because the forwarding, control, and management planes are all bundled together and, thus, administrators are supposed to deploy high-level policies, as each vendor has its own configuration methods. Software-Defined Networking (SDN) is considered the future paradigm of communication networks. It decouples control logic from its underlying hardware, thereby promoting logically centralized network control and making the network more programmable and easy to configure. Low-power wireless technologies are moving toward a multitenant and multiapplication Internet of Things (IoT), which requires an architecture with scalable, reliable, and configured solutions. However, employing an SDN-based centralized architecture in the environment of a low-power wireless IoT network introduces significant challenges, such as difficult-to-control traffic, unreliable links, network contention, and high associated overheads that can significantly affect the performance of the network. This paper is a contribution toward a performance evaluation for the use of SDN in wireless networking by evaluating the latency, packet drop ratio (PDR), data extraction rate (DER), and overheads. The results show that SDN adds a high percentage of overheads to the network, which is about 43% of the 57% user packets, and the DER drops when the number of mesh nodes are increased, in addition to the high loss that was observed for packets that traveled over more hops.

Downloads

Download data is not yet available.

Author Biographies

  • Zahraa Zakariya Saleh, Department of English, College of Education and Language, Lebanese French University, Erbil 44001, Kurdistan Region, Iraq.

    Zahraa Zakariya Saleh has received the MSc from the University of Kurdistan Hewler in 2019. Her research interest include SDN, low power network and lightweight network protocols.

  • Qahhar Muhammad Qadir, Department of Electrical Engineering, College of Engineering, Salahaddin University - Erbil, Erbil 44001, Kurdistan Region, Iraq. and Department of Computer Science and Engineering, School of Science and Engineering, University of Kurdistan Hewler, Erbil 44001, Kurdistan Region, Iraq.

    QAHHAR MUHAMMAD QADIR received the Ph.D. degree from the University of Southern Queensland, Toowoomba, QLD, Australia, in 2015. He is currently an academic with Salahaddin University-Erbil and University of Kurdistan Hewlêr. His current research interests include low-power wide area networks, Internet of Things, green communication, wireless/mobile networks, quality of service/QoE enhancement, and multimedia quality assessment.

References

20-bit, M. (n.d.). Retrieved from https://github.com/contiki-os/contiki/wiki/MSP430X.

Anadiotis, A.-C., Galluccio, L., Milardo, S., Morabito, G. & Palazzo, S. (2019). SD-WISE: A Software-Defined WIreless SEnsor network. Computer Networks. doi: https://doi.org/10.1016/j.comnet.2019.04.029

Asadollahi, S., Goswami, B. & Sameer, M. (2018, 2). Ryu controller's scalability experiment on software defined networks. 2018 IEEE International Conference on Current Trends in Advanced Computing (ICCTAC), (pp. 1–5). doi:10.1109/ICCTAC.2018.8370397

Asadollahi, S., Goswami, B., Raoufy, A. S. & Domingos, H. G. (2017, 12). Scalability of software defined network on floodlight controller using OFNet. 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), (pp. 1–5). doi:10.1109/ICEECCOT.2017.8284567

Baddeley, M., Nejabati, R., Oikonomou, G., Sooriyabandara, M. & Simeonidou, D. (2018, 6). Evolving SDN for Low-Power IoT Networks. 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft), (pp. 71–79). doi:10.1109/NETSOFT.2018.8460125

Baddeley, M., Raza, U., Stanoev, A., Oikonomou, G. C., Nejabati, R., Sooriyabandara, M., & Simeonidou, D. (2019). Atomic-SDN: Is Synchronous Flooding the Solution to Software-Defined Networking in IoT? IEEE Access, 7, 96019-96034.

Beacon. (n.d.). Retrieved from https://openflow.stanford.edu/display/Beacon

Costanzo, S., Galluccio, L., Morabito, G., & Palazzo, S. (2012, 10). Software Defined Wireless Networks: Unbridling SDNs. 2012 European Workshop on Software Defined Networking, (pp. 1–6). doi:10.1109/EWSDN.2012.12

de Oliveira, B. T., Alves, R. C., & Margi, C. B. (2015, 10). Software-defined Wireless Sensor Networks and Internet of Things standardization synergism. 2015 IEEE Conference on Standards for Communications and Networking (CSCN), (pp. 60–65). doi:10.1109/CSCN.2015.7390421

Dunkels, A., Gronvall, B. & Voigt, T. (2004, 11). Contiki - a lightweight and flexible operating system for tiny networked sensors. 29th Annual IEEE International Conference on Local Computer Networks, (pp. 455–462). doi:10.1109/LCN.2004.38

El-Mougy, A., Ibnkahla, M., & Hegazy, L. (2015, 10). Software-defined wireless network architectures for the Internet-of-Things. 2015 IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops), (pp. 804–811). doi:10.1109/LCNW.2015.7365931

Feamster, N., Rexford, J., & Zegura, E. (2014, 4). The Road to SDN: An Intellectual History of Programmable Networks. SIGCOMM Comput. Commun. Rev., 44, 87–98. doi:10.1145/2602204.2602219

Floodlight. (n.d.). Retrieved from http://floodlight.openflowhub.org/

Galluccio, L., Milardo, S., Morabito, G. & Palazzo, S. (2015, 4). Reprogramming Wireless Sensor Networks by using SDN-WISE: A hands-on demo. 2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), (pp. 19–20). doi:10.1109/INFCOMW.2015.7179322

Galluccio, L., Milardo, S., Morabito, G. & Palazzo, S. (2015, 4). SDN-WISE: Design, prototyping and experimentation of a stateful SDN solution for WIreless SEnsor networks. 2015 IEEE Conference on Computer Communications (INFOCOM), (pp. 513–521). doi:10.1109/INFOCOM.2015.7218418

Ghaleb, B., Al-Dubai, A.Y., Ekonomou, E., Alsarhan, A., Nasser, Y., Mackenzie, L.M. & Boukerche, A. (2019). A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-Power and Lossy Networks: A Focus on Core Operations. IEEE Communications Surveys Tutorials, 21, 1607–1635. doi:10.1109/COMST.2018.2874356

Helkey, J., Holder, L., & Shirazi, B. (2016). Comparison of simulators for assessing the ability to sustain wireless sensor networks using dynamic network reconfiguration. Sustainable Computing: Informatics and Systems, 9, 1–7. doi:https://doi.org/10.1016/j.suscom.2016.01.003

Hendrawan, I. N. & Arsa, I. G. (2017, 11). Zolertia Z1 energy usage simulation with Cooja simulator. 2017 1st International Conference on Informatics and Computational Sciences (ICICoS), (pp. 147–152). doi:10.1109/ICICOS.2017.8276353

iperf. (n.d.). Retrieved from https://iperf.fr/.

Jian, D., Chunxiu, X., Muqing, W., & Wenxing, L. (2017, 12). Design and implementation of a novel software-defined wireless sensor network. 2017 3rd IEEE International Conference on Computer and Communications (ICCC), (pp. 729–733). doi:10.1109/CompComm.2017.8322639

Lasso, F. F., Clarke, K., & Nirmalathas, A. (2018, 4). A software-defined networking framework for IoT based on 6LoWPAN. 2018 Wireless Telecommunications Symposium (WTS), (pp. 1–7). doi:10.1109/WTS.2018.8363938

Luo, T., Tan, H., & Quek, T. Q. (2012, 11). Sensor OpenFlow: Enabling Software-Defined Wireless Sensor Networks. IEEE Communications Letters, 16, 1896–1899. doi:10.1109/LCOMM.2012.092812.121712

Miguel, M., Jamhour, E., Pellenz, M., & Penna, M. (2018, 11). SDN architecture for 6LoWPAN wireless sensor networks. Sensors, 18, 3738. doi:10.3390/s18113738

msp430. (n.d.). Retrieved from https://github.com/pksec/msp430-gcc-4.7.3

Nikoukar, A., Raza, S., Poole, A., Güneş, M., & Dezfouli, B. (2018). Low-Power Wireless for the Internet of Things: Standards and Applications. IEEE Access, 6, 67893–67926. doi:10.1109/ACCESS.2018.2879189

NOX. (n.d.). Retrieved from https://github.com/noxrepo/nox.

OFNet. (n.d.). Retrieved from http://sdninsights.org/.

Ominike, A., Seun, E., A. O., A., & Osisanwo, F. (2016, 12). Introduction to Software Defined Networks (SDN). International Journal of Applied Information Systems, 11, 10–14. doi:10.5120/ijais2016451623

POX. (n.d.). Retrieved from http://www.noxrepo.org/pox/about-pox/.

Rowshanrad, S., Abdi, V. & Keshtgari, M. (2016, 11). Performance evaluation OF SDN controllers: Floodlight and Openday Light. IIUM Engineering Journal, 17, 47–57. doi:10.31436/iiumej.v17i2.615

Ryu. (n.d.). Retrieved from http://sdnhub.org/tutorials/ryu/

Theodorou, T., & Mamatas, L. (2017, 11). CORAL-SDN: A software-defined networking solution for the Internet of Things. 2017 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), (pp. 1–2). doi:10.1109/NFV-SDN.2017.8169870

Xia, W., Wen, Y., Foh, C., Niyato, D., & Xie, H. (2015, 1). A Survey on Software-Defined Networking. Communications Surveys & Tutorials, IEEE, 17, 27–51. doi:10.1109/COMST.2014.2330903

Zhao, Y., Iannone, L., & Riguidel, M. (2015, 11). On the performance of SDN controllers: A reality check. 2015 IEEE Conference on Network Function Virtualization and Software Defined Network (NFV-SDN), (pp. 79–85). doi:10.1109/NFV-SDN.2015.7387

Downloads

Published

2020-12-31

Issue

Vol. 4 No. 2 (2020): ISSUE 7

Section

Research Articles

License

Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License [CC BY-NC-ND 4.0] that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

How to Cite

The Downside of Software-Defined Networking in Wireless Network. (2020). UKH Journal of Science and Engineering, 4(2), 147-156. https://doi.org/10.25079/ukhjse.v4n2y2020.pp147-156