Softedgenet: SDN based energy-efficient distributed network architecture for edge computing
Abstract
The volume of data traffic has increased exponentially due to the explosive growth of IoT devices and the arrival of many new IoT applications. Due to the large volume of data generated from IoT devices, limited bandwidth, high latency, and realtime analysis requirements, the conventional centralized network architecture cannot meet users requirements. Intensive real-time data analysis is one of the major challenges in current state-ofthe- art centralized architectures due to the ubiquitous deployment of different types of sensors. To address the current challenges and adhere to the principles of architectural design, we are proposing a SoftEdgeNet model, which is a novel SDN-based distributed layered network architecture with a blockchain technique for a sustainable edge computing network. At the fog layer, we introduce an SDN-based secure fog node architecture to mitigate security attacks and provide real-time analytics services. We are also proposing a flow rule partition, and allocation algorithm at the edge of the network. The evaluation result shows our proposed model allows for a significant improvement of the interactions in real time data transmission. In terms of the ability to mitigate flooding attacks, the bandwidth is maintained above 9 Mb/s until the attack rates exceed 2000 PPS in the hardware environment and the bandwidth remained almost unchanged in the software environment. In the case of scalability of the proposed model, our proposed algorithm has performed better and proceeded linearly with the increase in traffic volume.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Recently, researchers have sought blockchain technology to integrate into decentralized SDN IoT framework to ensure uniform state among instances of the SDN controller.
“Recently, researchers [159,160] have sought blockchain technology to integrate into decentralized SDN IoT framework to ensure uniform state among the instances of the SDN controller.”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [160]
Cites
Blockchains and smart contracts for the internet of things
Christidis, K., & Devetsikiotis, M. (2016) · IEEE Access · doi:10.1109/access.2016.2566339 · Cited by 4,552 · see citing works
EdgeIoT: Mobile Edge Computing for the Internet of Things
Sun, X., & Ansari, N. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.1600492cm · Cited by 715 · see citing works
A Software Defined Fog Node Based Distributed Blockchain Cloud Architecture for IoT
Sharma, P. K., Chen, M.-Y., & Park, J. H. (2018) · IEEE Access · doi:10.1109/access.2017.2757955 · Cited by 676 · see citing works
Self-citationDistblocknet: a distributed blockchains-based secure SDN architecture for IoT networks
Sharma, P. K., Singh, S., Jeong, Y.-S., & Park, J. H. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1700041 · Cited by 428 · see citing works
Self-citationWhen things matter: A survey on data-centric internet of things
Qin, Y., Sheng, Q. Z., Falkner, N., Dustdar, S., Wang, H., & Vasilakos, A. V. (2016) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2015.12.016 · Cited by 331 · see citing works
Clarifying Fog Computing and Networking: 10 Questions and Answers
Chiang, M., Ha, S., Risso, F., Zhang, T., & Chih‐Lin, I. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.7901470 · Cited by 236 · see citing works
Palette: Distributing tables in software-defined networks
Kanizo, Y., Hay, D. A., & Keslassy, I. (2013) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infcom.2013.6566832 · Cited by 230 · see citing works
Software-Defined Wireless Networking Opportunities and Challenges for Internet-of-Things: A Review
Sood, K., Yu, S., & Xiang, Y. (2015) · IEEE Internet of Things Journal · doi:10.1109/jiot.2015.2480421 · Cited by 223 · see citing works
Infinite CacheFlow in software-defined networks
Katta, N. P. K., Alipourfard, O., Rexford, J., & Walker, D. (2014) · ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking (HotSDN) · doi:10.1145/2620728.2620734 · Cited by 170 · see citing works
Lu, R., Lin, X., Zhu, H., Liang, X., & Shen, X. (2011) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2011.95 · Cited by 166 · see citing works
Scalable rule management for data centers
Moshref, M., Yu, M., Sharma, A. B., & Govindan, R. (2013) · Cited by 86 · see citing works
Yan, B., Xu, Y., Xing, H., Xi, K., & Chao, H. J. (2014) · ACM SIGCOMM Workshop on Hot Topics in Software Defined Networking (HotSDN) · doi:10.1145/2620728.2620732 · Cited by 57 · see citing works
FS-OpenSecurity: A Taxonomic Modeling of Security Threats in SDN for Future Sustainable Computing
Sung, Y., Sharma, P. K., Lopez, E. M., & Park, J. H. (2016) · Sustainability · doi:10.3390/su8090919 · Cited by 31 · see citing works
Self-citationHeterogeneous Flow Table Distribution in Software-Defined Networks
Huang, J.-F., Chang, G.-Y., Wang, C., & Lin, C. (2015) · IEEE Transactions on Emerging Topics in Computing · doi:10.1109/tetc.2015.2457333 · Cited by 30 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
BlockIoTIntelligence: A Blockchain-enabled Intelligent IoT Architecture with Artificial Intelligence
Singh, S. K., Rathore, S., & Park, J. H. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2019.09.002 · Cited by 539 · see citing works
Self-citationA survey on the adoption of blockchain in IoT: challenges and solutions
Uddin, M. A., Stranieri, A., Gondal, I., & Balasubramanian, V. (2021) · Blockchain: Research and Applications · doi:10.1016/j.bcra.2021.100006 · Cited by 365 · see citing works
Rafique, W., Qi, L., Yaqoob, I., Imran, M. A., Rasool, R. U., & Dou, W. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2997475 · Cited by 365 · see citing works
Interaction of Edge-Cloud Computing Based on SDN and NFV for Next Generation IoT
Lv, Z., & Xiu, W. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2942719 · Cited by 238 · see citing works
Liu, X., Huang, H., Xiao, F., & Ma, Z. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2957421 · Cited by 211 · see citing works
Du, J., Jiang, C., Benslimane, A., Guo, S., & Ren, Y. (2022) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2022.3152150 · Cited by 194 · see citing works
Blockchain technology toward green IoT: opportunities and challenges
Sharma, P. K., Kumar, N., & Park, J. H. (2020) · IEEE Network · doi:10.1109/mnet.001.1900526 · Cited by 178 · see citing works
Self-citationA blockchain-based smart home gateway architecture for preventing data forgery
Lee, Y., Rathore, S., Park, J. H., & Park, J. H. (2020) · Human-centric Computing and Information Sciences · doi:10.1186/s13673-020-0214-5 · Cited by 154 · see citing works
Self-citationMedhane, D. V., Sangaiah, A. K., Hossain, M. S., Muhammad, G., & Wang, J. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2977196 · Cited by 151 · see citing works
Blockchain-SDN-Based Energy-Aware and Distributed Secure Architecture for IoT in Smart Cities
Islam, M. J., Rahman, A., Kabir, S., Karim, M. R., Acharjee, U. K., Nasir, M. K., Band, S. S., Sookhak, M., & Wu, S. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3100797 · Cited by 143 · see citing works
Edge AI for Internet of Energy: Challenges and perspectives
Himeur, Y., Sayed, A. N., Alsalemi, A., Bensaali, F., & Amira, A. (2023) · Internet of Things · doi:10.1016/j.iot.2023.101035 · Cited by 99 · see citing works
Denial of service attacks in edge computing layers: Taxonomy, vulnerabilities, threats and solutions
Uddin, R., Kumar, S., & Chamola, V. (2023) · Ad Hoc Networks · doi:10.1016/j.adhoc.2023.103322 · Cited by 97 · see citing works
IoT + AR: pervasive and augmented environments for “Digi-log” shopping experience
Jo, D., & Kim, G. J. (2019) · Human-centric Computing and Information Sciences · doi:10.1186/s13673-018-0162-5 · Cited by 95 · see citing works
A Survey on the Applications of Cloud Computing in the Industrial Internet of Things
Dritsas, E., & Τρίγκα, Μ. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9020044 · Cited by 88 · see citing works
Managing smart cities through six sigma DMADICV method: A review-based conceptual framework
Qayyum, S., Ullah, F., Al-Turjman, F. M., & Mojtahedi, M. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.103022 · Cited by 76 · see citing works
Edge computing in future wireless networks: A comprehensive evaluation and vision for 6G and beyond
Ergen, M., Saoud, B., Shayea, I. A. M., El‐Saleh, A. A., Ergen, O., Inan, F., & Tüysüz, M. F. (2024) · ICT Express · doi:10.1016/j.icte.2024.08.007 · Cited by 71 · see citing works
A Software-Defined IoT Device Management Framework for Edge and Cloud Computing
Mavromatis, A., Colman-Meixner, C., Silva, A. P., Vasilakos, X., Nejabati, R., & Simeonidou, D. E. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2949629 · Cited by 65 · see citing works
Alzoubi, Y. I., Gill, A., & Mishra, A. (2022) · Journal of Cloud Computing · doi:10.1186/s13677-022-00353-y · Cited by 60 · see citing works
Endogenous Trusted DRL-Based Service Function Chain Orchestration for IoT
Guo, S., Qi, Y., Jin, Y., Li, W., Qiu, X., & Meng, L. (2021) · IEEE Transactions on Computers · doi:10.1109/tc.2021.3051681 · Cited by 53 · see citing works
Securing SDN-Controlled IoT Networks Through Edge Blockchain
Hu, J., Reed, M. J., Thomos, N., Al-Naday, M., & Yang, K. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3017354 · Cited by 52 · see citing works
Social mining-based clustering process for big-data integration
Jung, H., & Chung, K. (2020) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-020-02042-7 · Cited by 44 · see citing works
Analysis of architectures implemented for IIoT
Oñate, W., & Sanz, R. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e12868 · Cited by 42 · see citing works
Reddy, D. K. K., Behera, H. S., Nayak, J., Naik, B., Ghosh, U., & Sharma, P. K. (2021) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2021.102866 · Cited by 42 · see citing works
Self-citationA Blockchain-Based Decentralized Composition Solution for IoT Services
Ridhawi, I. A., Aloqaily, M., Boukerche, A., & Jaraweh, Y. (2020) · International Conference on Communications · doi:10.1109/icc40277.2020.9149031 · Cited by 40 · see citing works
Integrating blockchain and Internet of Things systems: A systematic review on objectives and designs
Tran, N. K., Babar, M. A., & Boan, J. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102844 · Cited by 39 · see citing works
Distributed resource scheduling in edge computing: Problems, solutions, and opportunities
Sahni, Y., Cao, J., Yang, L., & Wang, S. (2022) · Computer Networks · doi:10.1016/j.comnet.2022.109430 · Cited by 38 · see citing works
Blockchain-based mobile edge computing system
Li, G., Ren, X., Wu, J., Ji, W., Yu, H., Cao, J., & Wang, R. (2021) · Information Sciences · doi:10.1016/j.ins.2021.01.050 · Cited by 38 · see citing works
Notions of architecture in fog computing
Mann, Z. Á. (2020) · Computing · doi:10.1007/s00607-020-00848-z · Cited by 33 · see citing works
Design and Simulation of an Edge Compute Architecture for IoT-Based Clinical Decision Support System
Kumar, R. H., & Rajaram, B. (2024) · IEEE Access · doi:10.1109/access.2024.3380906 · Cited by 30 · see citing works
Edge on Wheels With OMNIBUS Networking for 6G Technology
Ergen, M., Inan, F., Ergen, O., Shayea, I. A. M., Tüysüz, M. F., Azizan, A., Üre, N. K., & Nekovee, M. (2020) · IEEE Access · doi:10.1109/access.2020.3038233 · Cited by 25 · see citing works
Ahammad, I. (2023) · SN Computer Science · doi:10.1007/s42979-023-02235-9 · Cited by 24 · see citing works
Guo, S., Qi, Y., Yu, P., Xu, S., & Qi, F. (2020) · IEEE Network · doi:10.1109/mnet.011.2000028 · Cited by 23 · see citing works
Enforcing Optimal ACL Policies Using K-Partite Graph in Hybrid SDN
Amin, R., Shah, N., & Mehmood, W. (2019) · Electronics · doi:10.3390/electronics8060604 · Cited by 23 · see citing works
Blockchain-Fog Computing Integration Applications: A Systematic Review
Alzoubi, Y. I., & Aljaafreh, A. (2023) · Cybernetics and Information Technologies · doi:10.2478/cait-2023-0001 · Cited by 22 · see citing works
A Software-Defined-Networking-Enabled Approach for Edge-Cloud Computing in the Internet of Things
Dai, M., Su, Z., Li, R., & Yu, S. (2021) · IEEE Network · doi:10.1109/mnet.101.2100052 · Cited by 22 · see citing works
Moon, J., Yang, M., & Jeong, J. (2021) · Sensors · doi:10.3390/s21134553 · Cited by 19 · see citing works
Optimized task offloading strategy in IoT edge computing network
Birhanie, H. M., & Adem, M. (2024) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2024.101942 · Cited by 18 · see citing works
Techno-economic framework for dynamic operator selection in a multi-tier heterogeneous network
Bugár, G., Vološin, M., Maksymyuk, T., Zausinová, J., Gazda, V., Horváth, D., & Gazda, J. (2019) · Ad Hoc Networks · doi:10.1016/j.adhoc.2019.102007 · Cited by 17 · see citing works
Smart Manufacturing Scheduling System: DQN based on Cooperative Edge Computing
Moon, J., & Jeong, J. (2021) · International Conference on Ubiquitous Information Management and Communication (IMCOM) · doi:10.1109/imcom51814.2021.9377434 · Cited by 17 · see citing works
Blockchain-Aided Flow Insertion and Verification in Software Defined Networks
Hu, J., Reed, M., Al-Naday, M., & Thomos, N. (2020) · Global Internet of Things Summit (GIoTS) · doi:10.1109/giots49054.2020.9119638 · Cited by 15 · see citing works
SDN-enabled Quantized LQR for Smart Traffic Light Controller to Optimize Congestion
Sachan, A., & Kumar, N. (2024) · ACM Transactions on Internet Technology · doi:10.1145/3641104 · Cited by 14 · see citing works
iContinuum: An Emulation Toolkit for Intent-Based Computing Across the Edge-to-Cloud Continuum
Akbari, N., Toosi, A. N., Grundy, J., Khalajzadeh, H., Aslanpour, M. S., & Ilager, S. (2024) · IEEE ... International Conference on Cloud Computing · doi:10.1109/cloud62652.2024.00059 · Cited by 13 · see citing works
Optimal IoT Service Offloading with Uncertainty in SDN-Based Mobile Edge Computing
Hao, H., Zhang, J., & Gu, Q. (2021) · Mobile Networks and Applications · doi:10.1007/s11036-021-01796-4 · Cited by 13 · see citing works
Energy-Efficient Mobile Agent Protocol for Secure IoT Sustainable Applications
Elhoseny, M., Siraj, M., Haseeb, K., Nawaz, M., Altamimi, M. L., & Alghamdi, M. (2022) · Sustainability · doi:10.3390/su14148960 · Cited by 11 · see citing works
A blockchain-based trusted security zone architecture
Jo, J. H., Rathore, S., Loia, V., & Park, J. H. (2019) · The Electronic Library · doi:10.1108/el-02-2019-0053 · Cited by 11 · see citing works
Self-citationA DRL-based online real-time task scheduling method with ISSA strategy
Zhu, Z., Xu, H., He, Y., Pan, Z., Zhang, M., & Jian, C. (2024) · Cluster Computing · doi:10.1007/s10586-024-04426-2 · Cited by 9 · see citing works
Vishnu, V. M., & Manjunath, P. S. (2021) · Cyber-Physical Systems · doi:10.1080/23335777.2021.1992798 · Cited by 7 · see citing works
Resource Provisioning in Fog Computing - A Survey
Vetriveeran, D., & Leena Sri, R. (2025) · ACM Computing Surveys · doi:10.1145/3744662 · Cited by 6 · see citing works
Design and Evaluation of a Distributed Security Framework for the Internet of Things
Eze, K. G., & Akujuobi, C. M. (2022) · Journal of Signal and Information Processing · doi:10.4236/jsip.2022.131001 · Cited by 6 · see citing works
Smart Door Locking System Using IoT—A Security for Railway Engine Pilots
Sujatha, K., Bhavani, N. P. G., Jayalatsumi, U., Kavitha, T., Latha, B., Ganesan, A., & Kalaivani, A. (2023) · Advances in intelligent systems and computing · doi:10.1007/978-981-19-5443-6_20 · Cited by 3 · see citing works
Cross-Layer Architecture for Energy Optimization of Edge Computing
Uddin, R. S., Manifa, N. Z., Chakma, L., & Islam, M. M. (2023) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-34622-4_54 · Cited by 3 · see citing works
Prospective on Technical Considerations for Edge–Cloud Cooperation Using Software-Defined Networking
Singh, A., Bali, R. S., & Aujla, G. S. (2021) · Internet of things · doi:10.1007/978-3-030-89328-6_9 · Cited by 2 · see citing works
Artificial Intelligence with Enhanced Prospects by Blockchain in the Cyber Domain
Singh, P. K. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-16-8248-3_43 · Cited by 2 · see citing works
Privacy-Preserving MEC-Enabled Contextual Online Learning via SDN for Service Selection in IoT
Mu, D., Zhou, P., Li, Q., Li, R., & Xu, J. (2019) · IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS) · doi:10.1109/mass.2019.00042 · Cited by 2 · see citing works
Green blockchain for smart cities—an introduction
Verma, B., & Sharma, A. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-95407-5.00011-6 · Cited by 1 · see citing works
Comparative Evaluation of Cloud-Edge Security Architectures for Ddos Detection
Ceylan, M. F., Dalkılıç, G., & Özcanhan, M. H. (2025) · doi:10.1109/isctrkiye68593.2025.11224857 · Cited by 1 · see citing works
Artificial Intelligence with Enhanced Prospects by Blockchain in the Cyber Domain
Singh, P. K. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-16-8892-8_62 · Cited by 1 · see citing works
Yingfei, Y. (2021) · Mathematical Problems in Engineering · doi:10.1155/2021/5536997 · Cited by 1 · see citing works
RetractedDesign of Cloud Control System for Supply-oils of color Offset Press
Xiao-peng, Z., Cao, P., & Wang, M. (2021) · International journal of scientific and technology research
Enabling low‐latency service function chains by merging duplicate match operations
Zhang, D., Guo, K., Chen, X., & Liu, X. (2022) · IET Networks · doi:10.1049/ntw2.12049
QoS-Aware Computational Resource Allocation
Du, J., & Jiang, C. (2022) · Wireless networks · doi:10.1007/978-981-19-7648-3_10
Design and implementation of special sensor network for sewage treatment plant oriented to big data
Yu, L., Xie, X., Zhang, X., & Shi, C. (2022) · doi:10.1109/iip57348.2022.00077
OMN-IBUS Type of Networking System for the Communication System in 6G
Devi, A. S., Bhatt, D., Bansal, S., Keerthika, A., Mohanraj, T., & Santhosh, S. (2024) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite60783.2024.10616789
Architecture and Components of Edge Computing *
Xu, L., & Shi, W. (2025) · Wiley eBooks · doi:10.1002/9781394285860.ch3
Software defined network resource allocation for large-range edge-edge cooperation
Zhang, Z. (2026) · Computer Communications · doi:10.1016/j.comcom.2026.108548
- Authors
- Sharma, P. K., Rathore, S., Jeong, Y.-S., & Park, J. H.
- Affiliations
- Seoul National University of Science and Technology (KR)
- Dongguk University (KR)
- Venue
- IEEE Communications Magazine
- Published
- 2018-12
- Volume
- 56
- Issue
- 12
- Pages
- 104-111
- ISSN
- 0163-6804 (ISSN-L)
- 1558-1896
- OpenAlex
- W2893121585
- Cited by
- 67
- References
- 14
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 7 · 2023: 8 · 2022: 10 · 2021: 14 · 2020: 14 · 2019: 9
- FWCI
- 5.73
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Communications Magazine (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Keywords
- software-defined networking, edge computing, fog computing, distributed network architecture, blockchain, energy efficiency, Internet of Things, flooding attacks, real-time analytics, network security, scalability
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review