The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Survey on fog computing: architecture, key technologies, applications and open issues
Abstract
The emergence of Internet of Things (IoT) has enabled the interconnection and intercommunication among massive ubiquitous things, which caused an unprecedented generation of huge and heterogeneous amount of data, known as data explosions. On the other hand, although that cloud computing has served as an efficient way to process and store these data, however, challenges, such as the increasing demands of real time or latency-sensitive applications and the limitation of network bandwidth, still cannot be solved by using only cloud computing. Therefore, a new computing paradigm, known as fog computing, has been proposed as a complement to the cloud solution. Fog computing extends the cloud services to the edge of network, and makes computation, communication and storage closer to edge devices and end-users, which aims to enhance low-latency, mobility, network bandwidth, security and privacy. In this paper, we will overview and summarize fog computing model architecture, key technologies, applications, challenges and open issues. Firstly, we will present the hierarchical architecture of fog computing and its characteristics, and compare it with cloud computing and edge computing to emphasize the similarities and differences. Then, the key technologies like computing, communication and storage technologies, naming, resource management, security and privacy protection are introduced to present how to support its deployment and application in a detailed manner. Several application cases like health care, augmented reality, brain machine interface and gaming, smart environments and vehicular fog computing are also presented to further explain fog computing application scenarios. Finally, based on the observation, we propose some challenges and open issues which are worth further in-depth study and research in fog computing development.
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Cites
Edge computing: Vision and challenges
Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2579198 · Cited by 8,733
A survey of mobile cloud computing: architecture, applications, and approaches
Dinh, H. T., Lee, C., Niyato, D., & Wang, P. (2013) · Wireless Communications and Mobile Computing · doi:10.1002/wcm.1203 · Cited by 2,391
Mobile edge computing, Fog et al.: A survey and analysis of security threats and challenges
Roman, R., Lopez, J., & Mambo, M. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2016.11.009 · Cited by 1,338
Fog Computing: A Platform for Internet of Things and Analytics
Bonomi, F., Milito, R., Natarajan, P., & Zhu, J. (2014) · Studies in Computational Intelligence · doi:10.1007/978-3-319-05029-4_7 · Cited by 1,222
The Fog Computing Paradigm: Scenarios and Security Issues
Stojmenovic, I., & Wen, S. (2014) · Annals of Computer Science and Information Systems · doi:10.15439/2014f503 · Cited by 1,037
Fog Computing: Platform and Applications
Yi, S., Hao, Z., Qin, Z., & Li, Q. (2015) · 2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb) · doi:10.1109/hotweb.2015.22 · Cited by 829
Mobile fog: a programming model for large-scale applications on the internet of things
Hong, K., Lillethun, D., Ramachandran, U., Ottenwälder, B., & Koldehofe, B. (2013) · Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing · doi:10.1145/2491266.2491270 · Cited by 486
Towards wearable cognitive assistance
Ha, K., Chen, Z., Hu, W., Richter, W., Pillai, P., & Satyanarayanan, M. (2014) · Proceedings of the 12th annual international conference on Mobile systems, applications, and services · doi:10.1145/2594368.2594383 · Cited by 476
Emc: Emotion-aware mobile cloud computing in 5G
Chen, M., Zhang, Y., Li, Y., Mao, S., & Leung, V. C. M. (2015) · IEEE Network · doi:10.1109/mnet.2015.7064900 · Cited by 179
Fog computing architecture to enable consumer centric internet of things services
Datta, S. K., Bonnet, C., & Haerri, J. (2015) · 2015 International Symposium on Consumer Electronics (ISCE) · doi:10.1109/isce.2015.7177778 · Cited by 172
Cited by
All one needs to know about fog computing and related edge computing paradigms: A complete survey
Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., Kong, J., & Jue, J. P. (2019) · Journal of Systems Architecture · doi:10.1016/j.sysarc.2019.02.009 · Cited by 1,368
A Survey on Internet of Things and Cloud Computing for Healthcare
Dang, L. M., Piran, M. J., Han, D., Min, K., & Moon, H. (2019) · Electronics · doi:10.3390/electronics8070768 · Cited by 640
A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities
Capponi, A., Fiandrino, C., Kantarci, B., Foschini, L., Kliazovich, D., & Bouvry, P. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2914030 · Cited by 594
Enabling technologies for fog computing in healthcare IoT systems
Mutlag, A. A., Abd Ghani, M. K., Arunkumar, N., Mohammed, M. A., & Mohd, O. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2018.07.049 · Cited by 590
An Overview of Service Placement Problem in Fog and Edge Computing
Salaht, F. A., Desprez, F., & Lebre, A. (2021) · ACM Computing Surveys · doi:10.1145/3391196 · Cited by 336
Metadata
- Authors
- Hu, P., Dhelim, S., Ning, H., & Qiu, T.
- Venue
- Journal of Network and Computer Applications
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 98
- Pages
- 27-42
- ISSN
- 1084-8045 (ISSN-L)
- OpenAlex
- W2753968620
- Cited by
- 877
- References
- 10
- FWCI
- 61.82
- Type
- journal article
- Language
- en
- Open access
- closed
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