Journal of Soft Computing and Information Technology

Journal of Soft Computing and Information Technology

The Impact of Software-Defined Networks on Reducing Latency and Enhancing Data Security in Blockchain-Based IoT Architectures

Document Type : Persian Original Article

Author
Department of Computer Engineering, Payame Noor University (PNU), P. O. Box 19395-4697, Tehran, Iran
Abstract
The Internet of Things (IoT) is a network of objects interconnected via the Internet, enabling communication and information exchange among them to enhance the quality of human life. Despite its numerous advantages, IoT still faces challenges such as data security, privacy concerns, and high energy consumption of sensors. In this paper, a novel optimized hybrid architecture named "BlockC-SDOT" is proposed, leveraging blockchain and software-defined networking (SDN) architectures on a cloud computing platform for IoT. This innovative architecture combines a blockchain framework based on the Proof of Stake (PoS) consensus algorithm with SDN and cloud computing to enhance IoT performance and security. Through network clustering and cluster management via SDN, the architecture simultaneously addresses two critical parameters: sensor energy consumption and latency reduction in IoT networks. For enhanced security, the Diffie-Hellman algorithm and digital signatures are employed. Optimization is achieved using the Whale Optimization Algorithm (WOA) and the Jackson queueing model. To evaluate the efficiency of the proposed architecture, simulations are conducted to analyze various parameters, including latency, CPU performance under different attacks, throughput, energy consumption, packet arrival rate, and network bandwidth. These parameters are computed using the proposed method and compared against the results of the Ant Colony Optimization (ACO) and Genetic Algorithm (GA). Additionally, the latency of the proposed architecture is compared with the results obtained from RPL and CARP routing protocols. In both areas, the findings demonstrate the superiority and higher efficiency of the proposed hybrid approach over existing methods in the field.
Keywords

[1] R. Chataut, A. Phoummalayvane, and R. Akl, “Unleashing the Power of IoT: A Comprehensive Review of IoT Applications and Future Prospects in Healthcare, Agriculture, Smart Homes, Smart Cities, and Industry 4. 0,” Sensors, vol. 23, no. 16, p. 7194, Jan. 2023, doi: https: //doi. org/10. 3390/s23167194.
[2] Swati Sandeep Chopade, Hari Prabhat Gupta, and T. Dutta, “Survey on Sensors and Smart Devices for IoT Enabled Intelligent Healthcare System,” Jun. 2023, doi: https: //doi. org/10. 1007/s11277-023-10528-8.
[3] N. Gupta, M. S. Maashi, S. Tanwar, S. Badotra, M. Aljebreen, and S. Bharany, “A Comparative Study of Software Defined Networking Controllers Using Mininet,” Electronics, vol. 11, no. 17, p. 2715, Jan. 2022, doi: https: //doi. org/10. 3390/electronics11172715.
[4] V. A. Yakovlev, D. Z. Satybaldina, E. Egamberdiyev, and Y. Seitkulov, “Authentication and key distribution protocol based on Diffie-Hellman algorithm and physically unclonable function,” TELKOMNIKA (Telecommunication Computing Electronics and Control), vol. 22, no. 2, pp. 290–301, Apr. 2024.
[5] H. Farran, D. Khoury, and L. Bokor, “A comprehensive survey on the application of blockchain/hash chain technologies in V2X communications,” INFOCOMMUNICATIONS JOURNAL, vol. 14, no. 1, pp. 24–35, 2022, Accessed: Sep. 13, 2023. [Online]. Available: http: //real. mtak. hu/144581/.
[6] J. Xu, C. Wang, and X. Jia, “A Survey of Blockchain Consensus Protocols,” ACM Computing Surveys, Jan. 2023, doi: https: //doi. org/10. 1145/3579845.
[7] Wang, N., Zhou, Z., Liu, J., Deng, L., & Fu, J. (2024). Secure and Distributed IoV Data Sharing Scheme based on a Hybrid PoS Blockchain Protocol. IEEE Transactions on Vehicular Technology.
[8] S. Asaithambi et al. , “An Energy-Efficient and Blockchain-Integrated Software Defined Network for the Industrial Internet of Things,” Sensors, vol. 22, no. 20, p. 7917, Oct. 2022.
[9] S. A. Latif et al. , “AI-empowered, blockchain and SDN integrated security architecture for IoT network of cyber physical systems,” Computer Communications, vol. 181, pp. 274–283, Jan. 2022, doi: https: //doi. org/10. 1016/j. comcom. 2021. 09. 029.
[10]Ammar Muthanna et al. , “Secure IoT Network Structure Based on Distributed Fog Computing, with SDN/Blockchain,” Jan. 2019, doi: https: //doi. org/10. 20944/preprints201901. 0305. v1.
[11] N. Tekin, A. Acar, A. Aris, S. Uluagac, and V. Cagri , “Energy consumption of on-device machine learning models for IoT intrusion detection.
[12]A. Rahman, M. Jahidul Islam, Z. Rahman, and M. Mahfuz , “DistB-Condo: Distributed Blockchain-Based IoT-SDN Model for Smart Condominium,” Nov. 02, 2020.
[13] Z. A. El Houda, A. Hafid, and L. Khoukhi, “Co-IoT: A Collaborative DDoS Mitigation Scheme in IoT Environment Based on Blockchain Using SDN,” IEEE Xplore, Dec. 01, 2019.
[14]S. Misra, P. Kumar Deb, N. Pathak, and A. Mukherjee, “Blockchain-Enabled SDN for Securing Fog-Based Resource-Constrained IoT,” Aug. 10, 2020.
[15] Seyed Mostafa Bozorgi, Mahdi Rohani Hajiabadi, A. Asghar, and Arun Kumar Sangaiah, “Clustering based on whale optimization algorithm for IoT over wireless nodes,” Soft computing (Berlin. Print), vol. 25, no. 7, pp. 5663–5682, Jan. 2021.
[16]A. F. -X. Ametepe, A. S. R. M. Ahouandjinou, and E. C. Ezin, “Robust encryption method based on AES-CBC using elliptic curves Diffie–Hellman to secure data in wireless sensor networks,” Wireless Networks, vol. 28, no. 3, pp. 991–1001, Jan. 2022.
[17] M. D. Mohanty et al. , “Design of Smart and Secured Healthcare Service Using Deep Learning with Modified SHA-256 Algorithm,” Healthcare, vol. 10, no. 7, p. 1275, Jul. 2022.
[18]A. Ahmadi-Javid and M. Fathi, “Design of multi-service systems with facilities functioning as open Jackson queueing networks: application to online shopping stores,” OR Spectrum, Jun. 2022.
[19] W. Liang, L. Cui, and F. P. Tso, “Low-latency service function chain migration in edge-core networks based on open Jackson networks,” Journal of Systems Architecture, vol. 124, p. 102405, Mar. 2022, doi: https: //doi. org/10. 1016/j. sysarc. 2022. 102405.
[20] Wendl, M., Doan, M. H., & Sassen, R. (2023). The environmental impact of cryptocurrencies using proof of work and proof of stake consensus algorithms: A systematic review. Journal of Environmental Management, 326, 116530.
[21]  Alfriehat, N., Anbar, M., Aladaileh, M., Hasbullah, I., Shurbaji, T. A., Karuppayah, S., & Almomani, A. (2024). RPL-based attack detection approaches in IoT networks: review and taxonomy. Artificial Intelligence Review, 57(9), 248.
[22] Haseeb, S., Khalil Afzal, M., Tahir, M., Raza Jafri, M., & Raza, N. (2023). Energy‐efficient selection of relay for UWSNs in the Internet of underwater things. International Journal of Communication Systems, 36(18), e5619.
[23] Ran, X., Suyaroj, N., Tepsan, W., Ma, J., Zhou, X., & Deng, W. (2024). A hybrid genetic-fuzzy ant colony optimization algorithm for automatic K-means clustering in urban global positioning system. Engineering Applications of Artificial Intelligence, 137, 109237.
[24] Saiyed, M. F., & Al-Anbagi, I. (2024). A Genetic Algorithm-and t-Test-Based System for DDoS Attack Detection in IoT Networks. IEEE Access, 12, 25623-25641.
[25] Althiyabi, T., Ahmad, I., & Alassafi, M. O. (2024). Enhancing IoT Security: A Few-Shot Learning Approach for Intrusion Detection. Mathematics, 12(7), 1055.
[26]“DDoS 2019 | Datasets | Research | Canadian Institute for Cybersecurity | UNB,” www. unb. ca. https: //www. unb. ca/cic/datasets/ddos-2019. html.
[27] Arefin, S., Chowdhury, M., Parvez, R., Ahmed, T., Abrar, A. S., & Sumaiya, F. (2024, May). Understanding APT detection using Machine learning algorithms: Is superior accuracy a thing?. In 2024 IEEE International Conference on Electro Information Technology (eIT) (pp. 532-537). IEEE.
[28] Ali, J., Iwendi, C., Shan, G., Wu, H. C., Alenazi, M. J., Faheem, Z. B., & Biamba, C. N. (2024). Performance Optimization of Software-Defined Industrial Internet-of-Things (SD-IIoT). IEEE Access.
[29] Sinha, S. K. , Kumari, S. , Kataria, A. , Thangarasu, N. , & Sahoo, G. S. (2023). Blockchain empowerment: Investigating integration with software-defined networks and its impact on IoT privacy.  Multidisciplinary Reviews, 6.
[30] Kumaran, U. , Swetha, T. , Sharma, I. , Keerthana, R. , Tejashwini, V. , & Devarajan, G. G. (2024, May). Enhancing Cloud IoT Security With Blockchain and SDN. In 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE) (pp. 973-978). IEEE.
[31] Das, D. , Ghosh, U. , Evans, N. , & Shetty, S. (2024, June). Blockchain-Enabled Secure Device-to-Device Communication in Software-Defined Networking. In 2024 IEEE International Conference on Communications Workshops (ICC Workshops) (pp. 1450-1455). IEEE.