The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
A Survey on Edge and Edge-Cloud Computing Assisted Cyber-Physical Systems
Abstract
In recent years, the investigations on cyber-physical systems (CPS) have become increasingly popular in both academia and industry. A primary obstruction against the booming deployment of CPS applications lies in how to process and manage large amounts of generated data for decision making. To tackle this predicament, researchers advocate the idea of coupling edge computing, or edge-cloud computing into the design of CPS. However, this coupling process raises a diversity of challenges to the quality-of-services (QoS) of CPS applications. In this article, we present a survey on edge computing or edge-cloud computing assisted CPS designs from the QoS optimization perspective. We first discuss critical challenges in service latency, energy consumption, security, privacy, and reliability during the integration of CPS with edge computing or edge-cloud computing. Afterwards, we give an overview on the state-of-the-art works tackling different challenges for QoS optimization, and present a systematic classification during outlining literature for highlighting their similarities and differences. We finally summarize the experiences learned from surveyed works and envision future research directions on edge computing or edge-cloud computing assisted CPS optimization.
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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
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Next generation cloud computing: New trends and research directions
Varghese, B., & Buyya, R. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2017.09.020 · Cited by 857
Optimal Workload Allocation in Fog-Cloud Computing Towards Balanced Delay and Power Consumption
Deng, R., Lu, R., Lai, C., Luan, T. H., & Liang, H. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2565516 · Cited by 676
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Industrial Cyberphysical Systems: A Backbone of the Fourth Industrial Revolution
Colombo, A. W., Karnouskos, S., Kaynak, O., Shi, Y., & Yin, S. (2017) · IEEE Industrial Electronics Magazine · doi:10.1109/mie.2017.2648857 · Cited by 399
Self-citationCost Efficient Resource Management in Fog Computing Supported Medical Cyber-Physical System
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Status report on the second round of the NIST post-quantum cryptography standardization process
Moody, D., Alagic, G., Apon, D. C., Cooper, D. A., Dang, Q. H., Kelsey, J. M., Liu, Y.-K., Miller, C. A., Peralta, R. C., Perlner, R. A., et al. (2020) · doi:10.6028/nist.ir.8309 · Cited by 296
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Completion Time and Energy Optimization in the UAV-Enabled Mobile-Edge Computing System
Zhan, C., Hu, H., Sui, X., Liu, Z., & Niyato, D. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2993260 · Cited by 283
Cited by
Cicceri, G., Tricomi, G., D’Agati, L., Longo, F., Merlino, G., & Puliafito, A. (2023) · Sensors · doi:10.3390/s23094549 · Cited by 58
Cao, Z., Liu, B., Gao, D., Zhou, D., Han, X., & Cao, J. (2025) · Electronics · doi:10.3390/electronics14091843 · Cited by 7
“This integration has gradually led to the development of a collaborative cloud–edge architecture [2,3].”
Metadata
- Authors
- Cao, K., Hu, S., Shi, Y., Colombo, A., Karnouskos, S., & Li, X.
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2021-11
- Volume
- 17
- Issue
- 11
- Pages
- 7806-7819
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W3156772560
- Cited by
- 303
- References
- 48
- FWCI
- 22.59
- Type
- journal article
- Language
- en
- Open access
- closed
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- Cao, K., Hu, S., Shi, Y., Colombo, A., Karnouskos, S., & Li, X. (2021). A Survey on Edge and Edge-Cloud Computing Assisted Cyber-Physical Systems. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2021.3073066
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