The DOI matches its Crossref record; 83 of the 90 references it cites were found in a registry or an index.
Edge computing for Internet of Things: A survey, e-healthcare case study and future direction
Overview
Integrity signals
Registry
Cites
Statistics
Verification
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?
In the citing paper
“For example, OPC-UA has been applied widely for edgeIoT scenarios [210].”
From Federated Learning for Internet of Things: A Comprehensive Survey (2021) · cites this paper as [210]
In the citing paper
“Edge computing can be vital in times like the flu pandemic, where clinicians can monitor patients' vitals from remote areas and devise an action plan.”
From Medical 4.0 technologies for healthcare: Features, capabilities, and applications (2022) · cites this paper as [220]
In the citing paper
“Providing adequate healthcare to distant rural regions has always been difficult [219,220].”
From Medical 4.0 technologies for healthcare: Features, capabilities, and applications (2022) · cites this paper as [220]
In the citing paper
“In healthcare, edge computing is particularly useful in applications that require real-time monitoring and decision making, such as wearable devices for patient monitoring and remote diagnosis and treatment [7,8].”
From Edge AI for Early Detection of Chronic Diseases and the Spread of Infectious Diseases: Opportunities, Challenges, and Future Directions (2023) · cites this paper as [7]
Citations
Cites
McKeown (2008) · doi:10.1145/1355734.1355746 · Cited by 8,513
A Survey on Mobile Edge Computing: The Communication Perspective
Mao, Y., You, C., Zhang, J., Huang, K., & Letaief, K. B. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2745201 · Cited by 5,607
An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends
Zheng, Z., Xie, S., Dai, H., Chen, X., & Wang, H. (2017) · 2017 IEEE International Congress on Big Data (BigData Congress) · doi:10.1109/bigdatacongress.2017.85 · Cited by 4,515
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
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
Fog and IoT: An Overview of Research Opportunities
Chiang, M., & Zhang, T. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2584538 · Cited by 2,362
MAUI: making smartphones last longer with code offload
Cuervo, E., Balasubramanian, A., Cho, D.-K., Wolman, A., Saroiu, S., Chandra, R., & Bahl, P. (2010) · Proceedings of the 8th international conference on Mobile systems, applications, and services · doi:10.1145/1814433.1814441 · Cited by 2,281
(2011) · doi:10.1145/1966445.1966473 · Cited by 1,870
A survey of information-centric networking
Ahlgren, B., Dannewitz, C., Imbrenda, C., Kutscher, D., & Ohlman, B. (2012) · IEEE Communications Magazine · doi:10.1109/mcom.2012.6231276 · Cited by 1,630
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
Research works printed but not linked: 4
- El-Sayed, 2018, vol. 6
- 2018, vol. 19
- Ray, 2017, Data analytics: India needs agency for health data, Curr. Sci., 112, 1082
- Ray, 2017, Understanding the Role of Internet of Things Towards Providing Smart e-Healthcare Services, Bio Med. Res., 28, 1604
Cited by
Sorted by citations
Federated Learning for Internet of Things: A Comprehensive Survey
Nguyen, D. C., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., & Vincent Poor, H. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3075439 · Cited by 1,503
“For example, OPC-UA has been applied widely for edgeIoT scenarios [210].”
Federated Learning for Internet of Things: A Comprehensive Survey
Nguyen, D., Ding, M., Pathirana, P. N., Seneviratne, A., Li, J., & Poor, H. (2021) · Deakin Research Online (Deakin University) · Cited by 889
Pham, Q., Fang, F., Ha, V. N., Piran, M. J., Le, M., Le, L. B., Hwang, W., & Ding, Z. (2020) · IEEE Access · doi:10.1109/access.2020.3001277 · Cited by 887
Himeur, Y., Elnour, M., Fadli, F., Meskin, N., Petri, I., Rezgui, Y., Bensaali, F., & Amira, A. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10286-2 · Cited by 630
A systematic review of IoT in healthcare: Applications, techniques, and trends
Haghi Kashani, M., Madanipour, M., Nikravan, M., Asghari, P., & Mahdipour, E. (2021) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2021.103164 · Cited by 491
Metadata
- Authors
- Ray, P. P., Dash, D., & De, D.
- Affiliations
- Sikkim University (IN)
- National Institute of Technology Patna (IN)
- Maulana Abul Kalam Azad University of Technology, West Bengal (IN)
- Corresponding author
- Ray, Partha Pratim
- Venue
- Journal of Network and Computer Applications
- Publisher
- Elsevier BV
- Published
- 2019-08
- Volume
- 140
- Pages
- 1-22
- ISSN
- 1084-8045 (ISSN-L)
- OpenAlex
- W2944604407
- Cited by
- 241
- References
- 90
- Citations by year
- 2026: 13 · 2025: 35 · 2024: 40 · 2023: 36 · 2022: 45 · 2021: 39 · 2020: 26 · 2019: 7
- FWCI
- 16.02
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Network and Computer Applications (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
- Keywords
- edge computing, Internet of Things, e-health, smart healthcare, latency reduction, bandwidth reduction, smart sensors, smart cities, testbed
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.
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