The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Serving at the Edge: A Scalable IoT Architecture Based on Transparent Computing
Abstract
By moving service provisioning from the cloud to the edge, edge computing becomes a promising solution in the era of IoT to meet the delay requirements of IoT applications, enhance the scalability and energy efficiency of lightweight IoT devices, provide contextual information processing, and mitigate the traffic burdens of the backbone network. However, as an emerging field of study, edge computing is still in its infancy and faces many challenges in its implementation and standardization. In this article, we study an implementation of edge computing, which exploits transparent computing to build scalable IoT platforms. Specifically, we first propose a transparent computing based IoT architecture, and clearly identify its advantages and associated challenges. Then, we present a case study to clearly show how to build scalable lightweight wearables with the proposed architecture. Some future directions are finally pointed out to foster continued research efforts.
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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
Fog computing and its role in the internet of things
Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012) · Proceedings of the first edition of the MCC workshop on Mobile cloud computing · doi:10.1145/2342509.2342513 · Cited by 6,244
The case for vm-based cloudlets in mobile computing
Satyanarayanan, M., Bahl, P., Caceres, R., & Davies, N. (2009) · IEEE Pervasive Computing · doi:10.1109/mprv.2009.82 · Cited by 3,660
Cited by
Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing
Li, H., Ota, K., & Dong, M. (2018) · IEEE Network · doi:10.1109/mnet.2018.1700202 · Cited by 1,566
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
Al-Garadi, M. A., Mohamed, A., Al-Ali, A. K., Du, X., Ali, I., & Guizani, M. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2988293 · Cited by 1,392
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
An Overview on Edge Computing Research
Cao, K., Liu, Y., Meng, G., & Sun, Q. (2020) · IEEE Access · doi:10.1109/access.2020.2991734 · Cited by 1,254
Ren, J., Zhang, D., He, S., Zhang, Y., & Li, T. (2020) · ACM Computing Surveys · doi:10.1145/3362031 · Cited by 615
Self-citation
Metadata
- Authors
- Ren, J., Guo, H., Xu, C., & Zhang, Y.
- Venue
- IEEE Network
- Published
- 2017
- Volume
- 31
- Issue
- 5
- Pages
- 96-105
- ISSN
- 0890-8044 (ISSN-L)
- OpenAlex
- W2744588164
- Cited by
- 416
- References
- 3
- FWCI
- 43.66
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ren, J., Guo, H., Xu, C., & Zhang, Y. (2017). Serving at the Edge: A Scalable IoT Architecture Based on Transparent Computing. IEEE Network. https://doi.org/10.1109/mnet.2017.1700030
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