International Journal of Wireless and Microwave Technologies (IJWMT)
IJWMT Vol. 14, No. 5, 8 Oct. 2024
Cover page and Table of Contents: PDF (size: 614KB)
Heuristic – Driven Disjoint Alternate Path Switching – Based Fault Resilient Multi- Constraints Routing Protocol for SDN-mIOT
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Author(s)
Suprith Kumar K. S.
1,*
Eesha D.
1
Pooja A. P.
1
Monika Sharma D.
1
Index Terms
Software Defined Network, Internet-of-Things, Disjoint Alternate Forwarding Path, Heuristic Optimization, Quality-of-Service
Abstract
The last few years have witnessed exponential rise in internet-of-things (IoT) systems for communication; yet, ensuring quality-of-service (QoS) and transmission reliability over mobile topology has remained challenge. Despite the fact that the use of software defined networks (SDN) have enabled IoTs to achieve resource efficiency and reliability; it doesn’t guarantee optimality of the solution over the network with high dynamism and non-linearity. Moreover, the major at hand SDN-IoT protocols have applied standalone node parameters to perform routing and allied transmission decision that confine its robustness over dynamic network topologies. Interestingly, none of the state-of-art SDN-IoT protocols could address the problem of iterative link-outage and corresponding network discovery cost. Furthermore, even multi-path selection strategies too failed in addressing the problem of joined shortest path selection and allied iterative link-outage due to the common node failure. Considering it as motivation, in this paper a novel and robust Heuristic-Driven Disjoint Alternate Path Switching -based Fault-Resilient Multi-Constraints Routing Protocol for SDN-mIOT system (HDAP-SDNIoT) is proposed. HDAP-SDNIoT exploits multiple dynamic parameters like medium access control information, flooding and congestion probability information. HDAP-SDNIoT exploits aforesaid node parameters to perform node profiling that serves multi-constraints best forwarding path selection. The proposed model retrieves multiple best alternating paths which are fed as input to the Adaptive Genetic Algorithm (AGA) that retains three disjoint best forwarding paths. HDAP-SDNIoT protocol at first avoids any malicious node(s) to become forwarding node, while it provides auto-switching capability to the forwarding node to select a disjoint forwarding alternate path in case of any link-outage in current forwarding path. _Simulation results confirm robustness of the proposed model in terms of high packet delivery rate of 96.5%, low packet loss rate 3.5% and low delay of 211 ms that affirms its suitability towards real-time SDN-mIoT applications.
Cite This Paper
Suprith Kumar K. S., Eesha D., Pooja A. P., Monika Sharma D., "Heuristic – Driven Disjoint Alternate Path Switching – Based Fault Resilient Multi- Constraints Routing Protocol for SDN-mIOT", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.14, No.5, pp. 12-30, 2024. DOI:10.5815/ijwmt.2024.05.02
Reference
[1]J. Guerrero-Ibanez, S. Zeadally,J. Contreras-Castillo, “Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies,” IEEE Wireless Communications, vol. 22. 6,pp. 122–128, Dec. 2015.
[2]Oxford Dictonary, “Definition of Internet of Things in English,” 2018. [Online]. Available: https://en.oxforddictionaries.com/definition/internet of things
[3]Cambridge Dictonary, “The Internet of Things definition,” 2018. [Online]. Available: https://dictionary.cambridge.org/us/dictionary/english/internet-of-things
[4]Gartner IT Glossary, “The Internet of Things defined,” 2018. [Online]. Available: https://www.gartner.com/it-glossary/internet-of-things/
[5]Luigi Atzori, Antonio Iera, and Giacomo Morabito. “The internet of things: A survey”. In: Computer networks 54.15 (2010), pp. 2787–2805.
[6]Lili Yang, Shuang-Hua Yang, and Linda Plotnick. “How the internet of things technology enhances emergency response operations”. In: Technological Forecasting and Social Change 80.9 (2013), pp. 1854–1867.
[7]J. Pan, R. Jain, S. Paul, T. Vu, A. Saifullah, and M. Sha, “An Internet of Things Framework for Smart Energy in Buildings: Designs, Prototype, and Experiments,” IEEE Internet of Things Journal, vol. 2, no. 6, pp. 527–537, Dec. 2015.
[8]Rahman, A., Chakraborty, C., Anwar, A., Karim, M., Islam, M., Kundu, D., Rahman, Z., Band, S.S., et al.: Sdn-iot empowered intelligent framework for industry 4.0 applications during covid19 pandemic. Clust. Comput. (2021). https://doi.org/10.1007/ s10586-021-03367-4
[9]M. M. Raikar, S. M. Meena and M. M. Mulla, “Software Defined Internet of Things using lightweight protocol” Third International Conference on Computing and Network Communications (CoCoNet, 19, Procedia Computer Science 171 (2020) 1409–1418.
[10]K. Sood, S. Yu and Y. Xiang, "Software-Defined Wireless Networking Opportunities and Challenges for Internet-of-Things: A Review," in IEEE Internet of Things Journal, vol. 3, no. 4, pp. 453-463, Aug. 2016.
[11]Slavica Tomovic, Kenji Yoshigoe, Ivo Maljevic, and Igor Radusinovic. 2017. Software-Defined Fog Network Architecture for IoT. Wirel. Pers. Commun. 92, 1 (January 2017), 181-196.
[12]S. Al-Rubaye, E. Kadhum, Q. Ni and A. Anpalagan, "Industrial Internet of Things Driven by SDN Platform for Smart Grid Resiliency," in IEEE Internet of Things Journal.
[13]Lin, Ying-Dar et al. “SAMF: An SDN-Based Framework for Access Point Management in Large-scale Wi-Fi Networks.” Journal of Communications Software and Systems, Vol. 13 No. 4, 2017. https://doi.org/10.24138/jcomss.v13i4.398
[14]B. O. Kahjogh and G. Bernstein, "Energy and latency optimization in software defined wireless networks," 2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), Milan, 2017, pp. 714-719.doi: 10.1109/ICUFN.2017.7993884
[15]M. Al Ja’afreh, H. Adhami, A. E. Alchalabi, M. Hoda, and A. E. Saddik, “Toward integrating software defined networks with the Internet of Things: a review”, Cluster Computing, Springer, 2022, Vol. 25, pp. 1619–1636
[16]Fancy, C., Pushpalatha, M.: Traffic-aware adaptive server load balancing for software defined networks. Int. J. Electr. Comput. Eng. (2088-8708) 11(3), 2211–2218 (2021)
[17]Saha, N., Bera, S., Misra, S.: Sway: Traffic-aware QoS routing in software-defined iot. IEEE Trans. Emerg. Top. Comput. 9, 390–401 (2018a)
[18]Saha, N., Misra, S., Bera, S.: Qos-aware adaptive flow-rule aggregation in software-defined iot. In: 2018 IEEE global communications conference (GLOBECOM), IEEE, pp 206–212 (2018b).
[19]Qin, Z., Denker, G., Giannelli, C., Bellavista, P., Venkatasubramanian, N.: A software defined networking architecture for the internet-of-things. In: 2014 IEEE network operations and management symposium (NOMS), IEEE, pp 1–9 (2014)
[20]Mun˜oz, R., Vilalta, R., Yoshikane, N., Casellas, R., Martı´nez, R., Tsuritani, T., Morita, I.: Iot-aware multi-layer transport sdn and cloud architecture for traffic congestion avoidance through dynamic distribution of iot analytics. In: 2017 European conference on optical communication (ECOC), IEEE, pp 1–3 (2017)
[21]Gupta, H., Nath, S.B., Chakraborty, S., Ghosh, S.K.: Sdfog: A software defined computing architecture for qos aware service orchestration over edge devices. Preprint at arXiv:160901190 (2016)
[22]Llopis, J.M., Pieczerak, J., Janaszka, T.: Minimizing latency of critical traffic through sdn. In: 2016 IEEE international conference on networking, architecture and storage (NAS), IEEE, pp 1–6 (2016)
[23]Tomovic, S., Yoshigoe, K., Maljevic, I., Radusinovic, I.: Software-defined fog network architecture for iot. Wirel. Pers. Commun. 92(1), 181–196 (2017)
[24]Sawashima, H.: Characteristics of udp packet loss: effect of tcp traffic. proc of INET’97. (1997)
[25]Misra, S., Saha, N.: Detour: dynamic task offloading in softwaredefined fog for iot applications. IEEE J. Sel. Areas Commun. 37(5), 1159–1166 (2019)
[26]Yen, J.Y.: Finding the k shortest loopless paths in a network. Manage. Sci. 17(11), 712–716 (1971)
[27]Bera, S., Misra, S., Saha, N.: Traffic-aware dynamic controller assignment in sdn. IEEE Trans. Commun. 68(7), 4375–4382 (2020)
[28]Bizanis, N., Kuipers, F.A.: Sdn and virtualization solutions for the internet of things: a survey. IEEE Access 4, 5591–5606 (2016)
[29]Mao, B., Tang, F., Fadlullah, Z.M., Kato, N., Akashi, O., Inoue, T., Mizutani, K.: A novel non-supervised deep-learning-based network traffic control method for software defined wireless networks. IEEE Wirel. Commun. 25(4), 74–81 (2018)
[30]Das, S., Sahni, S.: Network topology optimization for data aggregation. In: 2014 14th IEEE/ACM international symposium on cluster, cloud and grid computing, pp. 493–501. IEEE, Piscataway (2014)
[31]Docker (2021) Docker. https://www.docker.com/. Accessed 1 Nov 2023.
[32]Kubernetes (2021) Kubernetes. https://kubernetes.io/. Accessed 1 Nov 2023.
[33]Sood, Keshav, Yu, Shui, Xiang, Yong and Peng, Sancheng 2016, Control layer resource management in SDN-IoT networks using multiobjective constraint, in ICIEA 2016: IEEE, Piscataway, N.J., pp. 71-76.
[34]A. A. Hayajneh, M. Z. A. Bhuiyan and I. McAndrew, “Improving Internet of Things (IoT) Security with Software-Defined Networking (SDN)”, MDPI, Computers 2020, 9, 8; doi:10.3390/computers9010008.
[35]A. Samanta, S. Bera, and S. Misra, “Link-Quality-Aware Resource Allocation with Load Balance in Wireless Body Area Networks,” IEEE Systems Journal, 2015, DOI: 10.1109/JSYST.2015.2458586.
[36]H. Sandor, B. Genge, and G. Sebestyen-Pal, “Resilience in the Internet of Things: The Software Defined Networking approach,” in Proc. of the IEEE Intl. Conf. on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, Sept. 2015, pp. 545–552.
[37]Y. Jararweh, M. Al-Ayyoub, A. Darabseh, E. Benkhelifa, M. Vouk, and A. Rindos, “SDIoT: a software defined based internet of things framework,” Journal of Ambient Intelligence and Humanized Computing, vol. 6, no. 4, pp. 453–461, Aug. 2015.