IoE Security Through Multi-Agent SDN

International Journal of Computer Trends and Technology (IJCTT)          
© 2021 by IJCTT Journal
Volume-69 Issue-12
Year of Publication : 2021
Authors : Kumar D and Mrs. C. Veni
  10.14445/22312803/IJCTT- V69I12P102


MLA Style: 
Kumar D and Mrs. C. Veni "IoE Security Through Multi-Agent SDN." International Journal of Computer Trends and Technology,  vol. 69, no. 12, Dec. 2021, pp.5-9.   Crossref ,

APA Style:
Kumar D & Mrs. C. Veni (2021). IoE Security Through Multi-Agent SDN. International Journal of Computer Trends and Technology, 69(12), 5-9.

The IoE is an intelligent connection of people, processes, data, and things (IoT). Thus IoE combines the converged networking/infrastructure with the process such as automation/orchestration and data science/analytics altogether for effective use by the people. IoE data is very vast and complicated, which could make available real instance environment and reactive information concerning such real things with reference to the environment. In order to retrieve significant and useful information from this massive IoE data, efficient frameworks are required which can be able to analyze the data satisfactorily. Therefore, advanced techniques are required for analyzing real-time, highly scalable data generated by IoT devices and enhancing security in the IoE environment. The SDN agent in a multiagent environment can implement edge node-specific security and data transfer policies that are framed specially for each IoT cluster of network devices. The proposed framework entitles agent-based modeling with SDN to provide enhanced security and automation. The data may even pass through multiple agents for different purposes with the cognitive orchestration mechanism to transfer data packets to the respective endpoint like cloud service or any other data plane.

IoE, Internet of Everything, security, SDN, multi-agent


[1] Akdogan, S. Indrakanti, U. Demiryurek, and C. Shahabi, Cost-efficient partitioning of spatial data on the cloud, 2015 IEEE International Conference on Big Data (Big Data), Santa Clara, CA, (2015) 501-506.
[2] The Internet of Things (IoT) – essential IoT business guide (n.d), retrieved from
[3] IOE (n.d), retrieved from
[4] Surendiran,R., and Alagarsamy,K., Privacy Conserved Access Control Enforcement in MCC Network with Multilayer Encryption. SSRG International Journal of Engineering Trends and Technology (IJETT), 4(5) (2013) 2217-2224.
[5] SDN Architecture (2014), retrieved from CH_1.0_06062014.pdf
[6] A. Akhunzada, A. Gani, N. B. Anuar, A. Abdelaziz, M. K. Khan, A. Hayat, and S. U. Khan, Secure and dependable software-defined networks, Journal of Network and Computer Applications, 61 (2016) 199–221.
[7] A. Akhunzada and M. K. Khan, Toward secure software-defined vehicular networks: Taxonomy, requirements, and open issues, IEEE Communications Magazine, 55(7) (2017) 110–118.
[8] Gartner‘s hype cycle special report for, (2011). Gartner Inc., 2012.
[9] A. Lapkin, Hype cycle for big data, retrieved from, (2012).
[10] A. Passito, E. Mota, R. Bennesby, and P. Fonseca, Agnos: A framework for autonomous control of software-defined networks, in 2014 IEEE 28th International Conference on Advanced Information Networking and Applications, (2014) 405–412. IEEE.
[11] S. Kuklinski, Programmable management framework for evolved sdn, in 2014 IEEE Network Operations and Management Symposium (NOMS) (2014) 1–8. IEEE.
[12] L. Ochoa-Aday, C. Cervello-Pastor, and A. Fern ´ and-Fern ´ Mendez, A distributed ´algorithm for topology discovery in software-defined networks, in International Conference on Practical Applications of Agents and Multi-Agent Systems, (2016) 363–367. Springer.
[13] V. Sharma, Multi-agent based intrusion prevention and mitigation architecture for software-defined networks, in 2017 International Conference on Information and Communication Technology Convergence (ICTC), (2017) 686–692, IEEE.
[14] I. Garc´ıa-Magarino and R. Lacuesta, Abs-trusts: An agent-based simulator of trust strategies in software-defined networks, Security and Communication Networks, 2017 (2017).
[15] Khan, Sahrish & Shah, Munam & Khan, Omair & Ahmed, Abdul. Software-Defined Network (SDN) Based Internet of Things (IoT): A Road Ahead. 1-8 (2017). 10.1145/3102304.3102319.
[16] Mervat Abu-Elkheir, Mohammad Hayajneh, and Najah Abu Ali, Data Management for the Internet of Things: Design Primitives and Solution‖, Sensors, (2013) 15582-15612.
[17] Q. Shafi, A. Basit, S. Qaisar, A. Koay, and I. Welch, Fog-assisted SDN controlled framework for enduring anomaly detection in an iot network, IEEE Access, 6 (2018) 73713–73723.
[18] A. Pektas¸ and T. Acarman, Deep learning to detect botnet via network flow summaries, Neural Computing and Applications, 31(11) (2019) 8021–8033.
[19] Bera. Samaresh, Mishra. Sudip, Roy. Sanku Kumar and Obaidat. Mohammad S., Soft-WSN: Software-Defined WSN Management System for IoT Applications, IEEE Systems Journal, 12(3) (2018) 2074–2081.
[20] D. Zhang, F. R. Yu, and R. Yang, A Machine Learning Approach for Software-Defined Vehicular Ad Hoc Networks with Trust Management, in 2018 IEEE Global Communications Conference (GLOBECOM), (2018) 1-6.
[21] Jae Gil Lee, Minseo Kang, ―Geospatial Big Data: Challenges and Opportunities‖, Journal of Big Data Research, 2(2) (2015) 74-81.