Multipath Routing Implementation in SD-IoT Network Using OpenFlow-based Routing Metrics

Muhammad Atthariq - University of Muhammadiyah Malang, Malang, Indonesia
Rizky Hidayat - University of Muhammadiyah Malang, Malang, Indonesia
Medina Sadida - University of Muhammadiyah Malang, Malang, Indonesia
Lailis Syafa'ah - University of Muhammadiyah Malang, Malang, Indonesia
Fauzi Sumadi - University of Muhammadiyah Malang, Malang, Indonesia

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The implementation growth of the Internet of Things (IoT) may increase the complexity of the data transmission process between smart devices. The route generation process between available nodes on the network will burden the intermediary node. One of the possible solutions for resolving the problem is the integration of Software Defined Networks and IoT (SD-IoT) to provide network automation and management. The separation of networking control and data forwarding functions may provide a multipath delivery path between each node in the IoT environment. In addition, the controller can directly extract the resource usage of the intermediary devices, which can be utilized as the routing metric variable in order to maintain the resource utilization on the intermediary devices. Instead of using traditional routing, this paper aims to develop multipath routing based on Deep First Search (DFS) and Dijkstra algorithms for acquiring an efficient path using OpenFlow-based routing metrics. The traffic monitoring module delivered the metrics extraction process, which obtained the variables using Port and Aggregate Flow Statistic features. The metrics calculation aimed to provide the multipath, which was constructed based on switches resource usage. Each selected path was chosen based on the smallest cost and probability provided by the group table feature in OpenFlow. The results showed that the Dijkstra algorithm could create the multipath more swiftly than DFS with a time difference of 0.6 s. The Quality of Service (QoS) results also indicated that the proposed routing metric variables could maintain the transmission process efficiently.


Multipath Routing; SDN; IoT; OpenFlow; Routing Metric

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N. Hossein Motlagh, M. Mohammadrezaei, J. Hunt, and B. Zakeri, “Internet of Things (IoT) and the Energy Sector,” Energies (Basel), vol. 13, no. 2, p. 494, Jan. 2020, doi: 10.3390/en13020494.

S. N. Swamy and S. R. Kota, “An Empirical Study on System Level Aspects of Internet of Things (IoT),” IEEE Access, vol. 8, pp. 188082–188134, 2020, doi: 10.1109/ACCESS.2020.3029847.

M. Pang, X. Yao, and M. Geng, “A computing resource scheduling strategy of massive IoT devices in the mobile edge computing environment,” The Journal of Engineering, vol. 2021, no. 6, pp. 348–357, Jun. 2021, doi: 10.1049/tje2.12040.

R. Thamilselvan, K. T. Selvi, R. R. Rajalaxmi, and E. Gothai, “Multipath Routing of Elephant Flows in Data Centers Based on Software Defined Networking,” Int J Eng Adv Technol, vol. 9, no. 2, pp. 2714–2717, Dec. 2019, doi: 10.35940/ijeat.B3258.129219.

G. A. Mutiara, N. Suryana, and O. Mohd, “WSN nodes power consumption using multihop routing protocol for illegal cutting forest,” TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 18, no. 3, p. 1529, Jun. 2020, doi: 10.12928/telkomnika.v18i3.14844.

P. A. Y. and R. Balakrishna, “Implementation of optimal solution for network lifetime and energy consumption metrics using improved energy efficient LEACH protocol in MANET,” TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 17, no. 4, p. 1758, Aug. 2019, doi: 10.12928/telkomnika.v17i4.12004.

N. Sultana, N. Chilamkurti, W. Peng, and R. Alhadad, “Survey on SDN based network intrusion detection system using machine learning approaches,” Peer Peer Netw Appl, vol. 12, no. 2, pp. 493–501, Mar. 2019, doi: 10.1007/s12083-017-0630-0.

M. M. Azmi and F. D. S. Sumadi, “Low-Rate Attack Detection on SD-IoT Using SVM Combined with Feature Importance Logistic Regression Coefficient,” Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Jun. 2022, doi: 10.22219/kinetik.v7i2.1405.

W. D. Nanda and F. D. S. Sumadi, “LRDDoS Attack Detection on SD-IoT Using Random Forest with Logistic Regression Coefficient,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 6, no. 2, pp. 220–226, Apr. 2022, doi: 10.29207/resti.v6i2.3878.

R. Wazirali, R. Ahmad, and S. Alhiyari, “SDN-OpenFlow Topology Discovery: An Overview of Performance Issues,” Applied Sciences, vol. 11, no. 15, p. 6999, Jul. 2021, doi: 10.3390/app11156999.

F. Rhamdani, N. A. Suwastika, and M. A. Nugroho, “Equal-Cost Multipath Routing in Data Center Network Based on Software Defined Network,” in 2018 6th International Conference on Information and Communication Technology (ICoICT), May 2018, pp. 222–226. doi: 10.1109/ICoICT.2018.8528730.

N. Ahmed and S. Misra, “Collaborative Flow-Identification Mechanism for Software-Defined Internet of Things,” IEEE Internet Things J, vol. 9, no. 5, pp. 3457–3464, Mar. 2022, doi: 10.1109/JIOT.2021.3099822.

J. Ali and B. Roh, “An Effective Approach for Controller Placement in Software-Defined Internet-of-Things (SD-IoT),” Sensors, vol. 22, no. 8, p. 2992, Apr. 2022, doi: 10.3390/s22082992.

T. Modi and P. Swain, “FlowDCN: Flow Scheduling in Software Defined Data Center Networks,” in 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), Feb. 2019, pp. 1–5. doi: 10.1109/ICECCT.2019.8869180.

X. Zhong, L. Zhang, and Y. Wei, “Dynamic Load-Balancing Vertical Control for a Large-Scale Software-Defined Internet of Things,” IEEE Access, vol. 7, pp. 140769–140780, 2019, doi: 10.1109/ACCESS.2019.2943173.

Md. S. Hossen, Md. H. Rahman, Md. Al-Mustanjid, Md. A. Shakil Nobin, and Md. A. Habib, “Enhancing Quality of Service in SDN based on Multi-path Routing Optimization with DFS,” in 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI), Dec. 2019, pp. 1–5. doi: 10.1109/STI47673.2019.9068057.

S. Syaifuddin, M. F. Azis, and F. D. S. Sumadi, “Comparison Analysis of Multipath Routing Implementation in Software Defined Network,” Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, May 2021, doi: 10.22219/kinetik.v6i2.1228.

C. Chen, F. Xue, Z. Lu, Z. Tang, and C. Li, “RLMR: Reinforcement Learning Based Multipath Routing for SDN,” Wirel Commun Mob Comput, vol. 2022, pp. 1–12, Feb. 2022, doi: 10.1155/2022/5124960.

S. L. Aljohani and M. J. F. Alenazi, “MPResiSDN: Multipath Resilient Routing Scheme for SDN-Enabled Smart Cities Networks,” Applied Sciences, vol. 11, no. 4, p. 1900, Feb. 2021, doi: 10.3390/app11041900.

D. Y. Setiawan, S. Naning Hertiana, and R. M. Negara, “6LoWPAN Performance Analysis of IoT Software-Defined-Network-Based Using Mininet-Io,” in 2020 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS), Jan. 2021, pp. 60–65. doi: 10.1109/IoTaIS50849.2021.9359714.

Md. T. Islam, N. Islam, and Md. al Refat, “Node to Node Performance Evaluation through RYU SDN Controller,” Wirel Pers Commun, vol. 112, no. 1, pp. 555–570, 2020, doi: 10.1007/s11277-020-07060-4.

S. Julius Fusic, P. Ramkumar, and K. Hariharan, “Path planning of robot using modified dijkstra Algorithm,” in 2018 National Power Engineering Conference (NPEC), Mar. 2018, pp. 1–5. doi: 10.1109/NPEC.2018.8476787.

M. Singh and G. Baranwal, “Quality of Service (QoS) in Internet of Things,” in 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU), Feb. 2018, pp. 1–6. doi: 10.1109/IoT-SIU.2018.8519862.

D. Silva, L. I. Carvalho, J. Soares, and R. C. Sofia, “A Performance Analysis of Internet of Things Networking Protocols: Evaluating MQTT, CoAP, OPC UA,” Applied Sciences, vol. 11, no. 11, p. 4879, May 2021, doi: 10.3390/app11114879.

N. Nikolov, “Research of MQTT, CoAP, HTTP and XMPP IoT Communication protocols for Embedded Systems,” in 2020 XXIX International Scientific Conference Electronics (ET), Sep. 2020, pp. 1–4. doi: 10.1109/ET50336.2020.9238208.

T. Tun, “A Forensics Analysis of ICMP Flooded DDoS Attack using WireShark,” Transactions on Networks and Communications, vol. 8, no. 3, pp. 08–15, Jun. 2020, doi: 10.14738/tnc.83.8250.

R. Jawaharan, P. M. Mohan, T. Das, and M. Gurusamy, “Empirical Evaluation of SDN Controllers Using Mininet/Wireshark and Comparison with Cbench,” in 2018 27th International Conference on Computer Communication and Networks (ICCCN), Jul. 2018, pp. 1–2. doi: 10.1109/ICCCN.2018.8487382.

P. Qiao, X. Wang, X. Yang, Y. Fan, and Z. Lan, “Joint Effects of Application Communication Pattern, Job Placement and Network Routing on Fat-Tree Systems,” in Proceedings of the 47th International Conference on Parallel Processing Companion, Aug. 2018, pp. 1–10. doi: 10.1145/3229710.3229747.

S. H. Mohammed and A. D. Jasim, “Evaluation of Firewall and Load balance in Fat-Tree Topology Based on Floodlight Controller,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 17, no. 3, p. 1157, Mar. 2020, doi: 10.11591/ijeecs.v17.i3.pp1157-1164.

Y. Ergiz, A. M. Demirtas, and T. Girici, “Joint multipath flow and layer allocation for scalable video streaming,” Computer Networks, vol. 191, p. 107995, May 2021, doi: 10.1016/j.comnet.2021.107995.


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