The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Edge Computing for the Internet of Things: A Case Study
Open accessAbstract
The amount of data generated by sensors, actuators, and other devices in the Internet of Things (IoT) has substantially increased in the last few years. IoT data are currently processed in the cloud, mostly through computing resources located in distant data centers. As a consequence, network bandwidth and communication latency become serious bottlenecks. This paper advocates edge computing for emerging IoT applications that leverage sensor streams to augment interactive applications. First, we classify and survey current edge computing architectures and platforms, then describe key IoT application scenarios that benefit from edge computing. Second, we carry out an experimental evaluation of edge computing and its enabling technologies in a selected use case represented by mobile gaming. To this end, we consider a resource-intensive 3-D application as a paradigmatic example and evaluate the response delay in different deployment scenarios. Our experimental results show that edge computing is necessary to meet the latency requirements of applications involving virtual and augmented reality. We conclude by discussing what can be achieved with current edge computing platforms and how emerging technologies will impact on the deployment of future IoT applications.
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Cites
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A Survey on Mobile Edge Computing: The Communication Perspective
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The case for vm-based cloudlets in mobile computing
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Mobile Edge Computing: A Survey on Architecture and Computation Offloading
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BackgroundFog 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
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Self-citationA survey of information-centric networking
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Cited by
Pham, Q.-V., Fang, F., Ha, V. N., Piran, M. J., Le, M., Le, L. B., Hwang, W.-J., & Ding, Z. (2020) · IEEE Access · doi:10.1109/access.2020.3001277 · Cited by 870
Neuromemristive Circuits for Edge Computing: A Review
Krestinskaya, O., James, A. P., & Chua, L. O. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2019.2899262 · Cited by 319
Towards edge computing in intelligent manufacturing: Past, present and future
Nain, G., Pattanaik, K. K., & Sharma, G. K. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.01.010 · Cited by 283
An Overview of Patient’s Health Status Monitoring System Based on Internet of Things (IoT)
Kadhim, K. T., Alsahlany, A. M., Wadi, S. M., & Kadhum, H. T. (2020) · Wireless Personal Communications · doi:10.1007/s11277-020-07474-0 · Cited by 267
Edge computing for Internet of Things: a survey, e-healthcare case study and future direction
Ray, P. P., Dash, D., & De, D. (2019) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2019.05.005 · Cited by 241
Metadata
- Authors
- Premsankar, G., Di Francesco, M., & Taleb, T.
- Venue
- IEEE Internet of Things Journal
- Published
- 2018-04
- Volume
- 5
- Issue
- 2
- Pages
- 1275-1284
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W2786027963
- Cited by
- 697
- References
- 46
- FWCI
- 48.39
- Type
- journal article
- Language
- en
- Open access
- green
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