The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing
Open accessAbstract
The Internet of Things (IoT) is a paradigm based on the Internet that comprises many interconnected technologies like RFID (Radio Frequency IDentification) and WSAN (Wireless Sensor and Actor Networks) in order to exchange information. The current needs for better control, monitoring and management in many areas, and the ongoing research in this field, have originated the appearance and creation of multiple systems like smart-home, smart-city and smart-grid. However, the limitations of associated devices in the IoT in terms of storage, network and computing, and the requirements of complex analysis, scalability, and data access, require a technology like Cloud Computing to supplement this field. Moreover, the IoT can generate large amounts of varied data and quickly when there are millions of things feeding data to Cloud Computing. The latter is a clear example of Big Data, that Cloud Computing needs to take into account. This paper presents a survey of integration components: Cloud platforms, Cloud infrastructures and IoT Middleware. In addition, some integration proposals and data analytics techniques are surveyed as well as different challenges and open research issues are pointed out.
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Citations
Cites
Internet of Things in industries: A survey
Xu, L. D., He, W., & Li, S. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2300753 · Cited by 5,172
Context Aware Computing for The Internet of Things: A Survey
Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2013.042313.00197 · Cited by 2,861 · cited 1×
“Context-aware computing allows us to store context information linked to sensor data allowing an easy and meaningful interpretation [93].”
BackgroundThe Constrained Application Protocol (CoAP)
Shelby, Z., Hartke, K., & Bormann, C. (2014) · doi:10.17487/rfc7252 · Cited by 2,605
Apache Hadoop YARN: yet another resource negotiator
Vavilapalli, V. K., Murthy, A. C., Douglas, C., Agarwal, S., Konar, M., Evans, R., Graves, T., Lowe, J., Shah, H., Seth, S., et al. (2013) · Proceedings of the 4th annual Symposium on Cloud Computing · doi:10.1145/2523616.2523633 · Cited by 1,848
Data Mining for Internet of Things: A Survey
Tsai, C.-W., Lai, C.-F., Chiang, M.-C., & Yang, L. T. (2014) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2013.103013.00206 · Cited by 620
Cited by
On blockchain and its integration with IoT. Challenges and opportunities
Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.05.046 · Cited by 1,908
Self-citationA 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
Internet of Things is a revolutionary approach for future technology enhancement: a review
Kumar, S., Tiwari, P., & Zymbler, M. (2019) · Journal of Big Data · doi:10.1186/s40537-019-0268-2 · Cited by 1,253
Internet of Things (IoT): A review of enabling technologies, challenges, and open research issues
Čolaković, A., & Hadžialić, M. (2018) · Computer Networks · doi:10.1016/j.comnet.2018.07.017 · Cited by 825
Security and privacy in smart farming: challenges and opportunities
Gupta, M., Abdelsalam, M., Khorsandroo, S., & Mittal, S. (2020) · IEEE Access · doi:10.1109/access.2020.2975142 · Cited by 609
Metadata
- Authors
- Díaz, M., Martín, C., & Rubio, B.
- Venue
- Journal of Network and Computer Applications
- Publisher
- Elsevier BV
- Published
- 2016-05
- Volume
- 67
- Pages
- 99-117
- ISSN
- 1084-8045 (ISSN-L)
- OpenAlex
- W2251418013
- Cited by
- 689
- References
- 5
- FWCI
- 95.38
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
