Blockchain and fog based architecture for internet of everything in smart cities
Open accessAbstract
Fog computing (FC) is used to reduce the energy consumption and latency for the heterogeneous communication approaches in the smart cities’ applications of the Internet of Everything (IoE). Fog computing nodes are connected through wired or wireless medium. The goal of smart city applications is to develop the transaction relationship of real-time response applications. There are various frameworks in real-world to support the IoE in smart-cities but they face the issues like security, platform Independence, multi-application assistance, and resource management. This article is motivated from the Blockchain and Fog computing technologies and presents a secured architecture Blockchain and Fog-based Architecture Network (BFAN) for IoE applications in the smart cities. The proposed architecture secures sensitive data with encryption, authentication, and Blockchain. It assists the System-developers and Architects to deploy the applications in smart city paradigm. The goal of the proposed architecture is to reduce the latency and energy, and ensure improved security features through Blockchain technology. The simulation results demonstrate that the proposed architecture performs better than the existing frameworks for smart-cities.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
Fog computing has emerged on the Internet of Everything to reduce energy consumption for IoT devices and significantly increase the processing time of the client's services.
“Fog computing has emerged on the Internet of Everything (IoE) to reduce energy consumption for IoT devices and significantly increase the processing time of the client's services [154].”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [154]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Internet of Things for Smart Cities
Zanella, A., Bui, N., Castellani, A. P., Vangelista, L., & Zorzi, M. (2014) · IEEE Internet of Things Journal · doi:10.1109/jiot.2014.2306328 · Cited by 6,385 · see citing works
Current trends in Smart City initiatives: Some stylised facts
Neirotti, P., De Marco, A., Cagliano, A. C., Mangano, G., & Scorrano, F. (2014) · Cities · doi:10.1016/j.cities.2013.12.010 · Cited by 2,322 · see citing works
Gupta, H., Vahid Dastjerdi, A., Ghosh, S. K., & Buyya, R. (2017) · Software: Practice and Experience · doi:10.1002/spe.2509 · Cited by 1,649 · see citing works
An Information Framework for Creating a Smart City Through Internet of Things
Jin, J., Gubbi, J., Marusic, S., & Palaniswami, M. S. (2014) · IEEE Internet of Things Journal · doi:10.1109/jiot.2013.2296516 · Cited by 1,318 · see citing works
Edge Computing for the Internet of Things: A Case Study
Premsankar, G., Francesco, M. D., & Taleb, T. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2805263 · Cited by 720 · see citing works
Smart farming IoT platform based on edge and cloud computing
Zamora, M. Á., Santa, J., Martinez, J. A., Martínez, V., & Skármeta, A. (2018) · Biosystems Engineering · doi:10.1016/j.biosystemseng.2018.10.014 · Cited by 503 · see citing works
Enabling smart cities through a cognitive management framework for the internet of things
Vlacheas, P. T., Giaffreda, R., Stavroulaki, V., Kelaidonis, D., Foteinos, V., Poulios, G., Demestichas, P., Somov, A., Biswas, A. R., & Moessner, K. (2013) · IEEE Communications Magazine · doi:10.1109/mcom.2013.6525602 · Cited by 408 · see citing works
Naranjo, P. G. V., Shojafar, M., Mostafaei, H., Pooranian, Z., & Baccarelli, E. (2016) · The Journal of Supercomputing · doi:10.1007/s11227-016-1785-9 · Cited by 287 · see citing works
Fog computing: from architecture to edge computing and big data processing
Singh, S. P., Nayyar, A., Kumar, R., & Sharma, A. (2018) · The Journal of Supercomputing · doi:10.1007/s11227-018-2701-2 · Cited by 240 · see citing works
Self-citationNaranjo, P. G. V., Pooranian, Z., Shojafar, M., Conti, M., & Buyya, R. (2018) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2018.07.003 · Cited by 231 · see citing works
Pastor, F. J. F., García‐Chamizo, J. M., Nieto-Hidalgo, M., et al. (2018) · Sensors · doi:10.3390/s18061731 · Cited by 213 · see citing works
A fog computing based smart grid model
Okay, F. Y., & Özdemi̇r, S. (2016) · International Symposium on Networks, Computers and Communications (ISNCC) · doi:10.1109/isncc.2016.7746062 · Cited by 196 · see citing works
Feasibility of Fog Computing Deployment based on Docker Containerization over RaspberryPi
Bellavista, P., & Zanni, A. (2017) · International Conference on Distributed Computing and Networking (ICDCN) · doi:10.1145/3007748.3007777 · Cited by 187 · see citing works
Vehicular delay-tolerant networks for smart grid data management using mobile edge computing
Kumar, N., Zeadally, S., & Rodrigues, J. J. P. C. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.7588230 · Cited by 178 · see citing works
A Fog Computing and Cloudlet Based Augmented Reality System for the Industry 4.0 Shipyard
Fernández‐Caramés, T. M., Fraga‐Lamas, P., Suárez-Albela, M., & Montesinos, M. (2018) · Sensors · doi:10.3390/s18061798 · Cited by 156 · see citing works
A Taxonomy and Future Directions for Sustainable Cloud Computing
Gill, S. S., & Buyya, R. (2018) · ACM Computing Surveys · doi:10.1145/3241038 · Cited by 150 · see citing works
On Enabling Sustainable Edge Computing with Renewable Energy Resources
Li, W., Yang, T., Delicato, F. C., et al. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1700888 · Cited by 149 · see citing works
Edge Computing with Cloud for Voice Disorder Assessment and Treatment
Muhammad, G., Alhamid, M. F., Alsulaiman, M., & Gupta, B. B. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1700790 · Cited by 137 · see citing works
Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes
Gia, T. N., Jiang, M., Sarker, V. K., Rahmani, A. M., Westerlund, T., Liljeberg, P., & Tenhunen, H. (2017) · International Wireless Communications and Mobile Computing Conference (IWCMC) · doi:10.1109/iwcmc.2017.7986551 · Cited by 132 · see citing works
Augmented reality based on edge computing using the example of remote live support
Schneider, M., Rambach, J., & Stricker, D. (2017) · 2017 IEEE International Conference on Industrial Technology (ICIT) · doi:10.1109/icit.2017.7915547 · Cited by 96 · see citing works
Green Internet of Things (G-IoT)
Solanki, A., & Nayyar, A. (2019) · Advances in data mining and database management book series · doi:10.4018/978-1-5225-7432-3.ch021 · Cited by 95 · see citing works
Self-citationDubey, H., Yang, J., Constant, N., Amiri, A. M., Yang, Q., & Mankodiya, K. (2015) · ASE BigData & SocialInformatics · doi:10.1145/2818869.2818889 · Cited by 90 · see citing works
Vallati, C., Virdis, A., Mingozzi, E., & Stea, G. (2016) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2016.2590100 · Cited by 69 · cited 2× · see citing works
“Vallati et al. [24] proposed a LTE based architecture for smart-home.”
BackgroundAuthentication Protocol for Cloud Databases Using Blockchain Mechanism
Deep, G., Mohana, R., Nayyar, A., Padmanaban, S., & Hossain, E. (2019) · Sensors · doi:10.3390/s19204444 · Cited by 67 · see citing works
Self-citationEfficient placement of edge computing devices for vehicular applications in smart cities
Premsankar, G., Ghaddar, B., Francesco, M. D., & Verago, R. (2018) · IEEE/IFIP Network Operations and Management Symposium (NOMS) · doi:10.1109/noms.2018.8406256 · Cited by 66 · see citing works
On Developing Smart Transportation Applications in Fog Computing Paradigm
Giang, N. K., Leung, V. C. M., & Lea, R. (2016) · Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications · doi:10.1145/2989275.2989286 · Cited by 59 · see citing works
Exploring device-to-device communication for mobile cloud computing
Li, Y., Sun, L., & Wang, W. (2014) · International Conference on Communications · doi:10.1109/icc.2014.6883656 · Cited by 53 · see citing works
Stack4Things as a fog computing platform for Smart City applications
Bruneo, D., Distefano, S., Longo, F., et al. (2016) · IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) · doi:10.1109/infcomw.2016.7562195 · Cited by 50 · see citing works
Dynamic Task Scheduling using Balanced VM Allocation Policy for Fog Computing Platforms
Singh, S. P., Nayyar, A., Channi, H. K., et al. (2019) · Scalable Computing Practice and Experience · doi:10.12694/scpe.v20i2.1538 · Cited by 50 · see citing works
Self-citationMultimedia Social Big Data: Mining
Kumar, A., Sangwan, S. R., & Nayyar, A. (2019) · Intelligent systems reference library · doi:10.1007/978-981-13-8759-3_11 · Cited by 49 · see citing works
Self-citationData Placement in Era of Cloud Computing: a Survey, Taxonomy and Open Research Issues
Kaur, A., Gupta, P., Singh, M., et al. (2019) · Scalable Computing Practice and Experience · doi:10.12694/scpe.v20i2.1530 · Cited by 44 · see citing works
Self-citationInnovative Ideas to Manage Urban Traffic Congestion in Cognitive Cities
Das, S., & Nayyar, A. (2019) · Practice, progress, and proficiency in sustainability · doi:10.4018/978-1-5225-8085-0.ch006 · Cited by 34 · see citing works
Self-citationCyber Security Challenges for Smart Cities
Nayyar, A., Jain, R., Mahapatra, B., et al. (2019) · Practice, progress, and proficiency in sustainability · doi:10.4018/978-1-5225-8085-0.ch002 · Cited by 31 · see citing works
Self-citationInnovation Opportunities through Internet of Things (IoT) for Smart Cities
Krishnamurthi, R., Nayyar, A., & Solanki, A. (2019) · CRC Press eBooks · doi:10.1201/9780429454837-13 · Cited by 29 · see citing works
Self-citationRameshwar, R., Solanki, A., Nayyar, A., et al. (2019) · Advances in civil and industrial engineering book series · doi:10.4018/978-1-5225-9754-4.ch007 · Cited by 28 · see citing works
Self-citationOn Building Smart City IoT Applications
Giang, N. K., Lea, R., Blackstock, M., et al. (2016) · doi:10.1145/3009912.3009919 · Cited by 23 · see citing works
A Taxonomy and Future Directions for Sustainable Cloud Computing: 360 Degree ViewPreprint
Gill, S. S., & Buyya, R. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1712.02899 · Cited by 21 · see citing works
Security and Privacy in Social Networks: Data and Structural Anonymity
Jain, R., Jain, N., & Nayyar, A. K. (2019) · Springer eBooks · doi:10.1007/978-3-030-22277-2_11 · Cited by 17 · see citing works
Self-citationProceedings of the 2nd International Workshop on Smart
(2016) · doi:10.1145/3009912 · Cited by 5 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Dubey, H.; Yang, J.; Constant, N.; Amiri, A.M.; Yang, Q.; Makodiya, K. Fog data: Enhancing telehealth big data through fog computing. In Proceedings of the ASE Bigdata & Socialinformatics 2015; ACM: New York, NY, USA, 2015; p. 14.
Cited by
Sorted by citations
A 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
EdgeMediChain: A Hybrid Edge Blockchain-Based Framework for Health Data Exchange
Akkaoui, R., Hei, X., & Cheng, W. (2020) · IEEE Access · doi:10.1109/access.2020.3003575 · Cited by 175 · see citing works
DistB-Condo: Distributed Blockchain-Based IoT-SDN Model for Smart Condominium
Rahman, A., Islam, M. J., Rahman, Z., Reza, M. M., Anwar, A., Mahmud, M. A. P., Nasir, M. K., & Noor, R. M. (2020) · IEEE Access · doi:10.1109/access.2020.3039113 · Cited by 66 · 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
- Authors
- Singh, P., Nayyar, A., Kaur, A., & Ghosh, U.
- Affiliations
- Lovely Professional University (IN)
- Duy Tan University (VN)
- Vanderbilt University (US)
- Corresponding author
- Nayyar, Anand
- Venue
- Future Internet
- Publisher
- MDPI AG
- Published
- 2020-03-26
- Volume
- 12
- Issue
- 4
- Pages
- 61
- ISSN
- 1999-5903 (ISSN-L)
- OpenAlex
- W3013411140
- Cited by
- 190
- References
- 39
- Citations by year
- 2026: 1 · 2025: 28 · 2024: 49 · 2023: 30 · 2022: 29 · 2021: 39 · 2020: 14
- FWCI
- 13.16
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Future Internet (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- blockchain, fog computing, Internet of Everything, smart cities, secure architecture, data encryption, authentication, latency reduction, energy consumption, resource management, heterogeneous communication
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