The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Middleware for Internet of Things: A Survey
Open accessAbstract
The Internet of Things (IoT) envisages a future in which digital and physical things or objects (e.g., smartphones, TVs, cars) can be connected by means of suitable information and communication technologies, to enable a range of applications and services. The IoT's characteristics, including an ultra-large-scale network of things, device and network level heterogeneity, and large numbers of events generated spontaneously by these things, will make development of the diverse applications and services a very challenging task. In general, middleware can ease a development process by integrating heterogeneous computing and communications devices, and supporting interoperability within the diverse applications and services. Recently, there have been a number of proposals for IoT middleware. These proposals mostly addressed wireless sensor networks (WSNs), a key component of IoT, but do not consider RF identification (RFID), machine-to-machine (M2M) communications, and supervisory control and data acquisition (SCADA), other three core elements in the IoT vision. In this paper, we outline a set of requirements for IoT middleware, and present a comprehensive review of the existing middleware solutions against those requirements. In addition, open research issues, challenges, and future research directions are highlighted.
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Cites
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×
“In fact, to minimize the impact of such devices on the environment and energy consumption, low-power radios are likely to be used for connection to the Internet.”
MOSDEN: An Internet of Things Middleware for Resource Constrained Mobile Devices
Perera, C., Jayaraman, P. P., Zaslavsky, A., Georgakopoulos, D., & Christen, P. (2014) · 2014 47th Hawaii International Conference on System Sciences · doi:10.1109/hicss.2014.137 · Cited by 145
Cited by
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
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
Machine learning based solutions for security of Internet of Things (IoT): A survey
Tahsien, S. M., Karimipour, H., & Spachos, P. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102630 · Cited by 470
Verma, S., Kawamoto, Y., Fadlullah, Z. M., Nishiyama, H., & Kato, N. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2694469 · Cited by 422
Dizdarević, J., Carpio, F., Jukan, A., & Masip-Bruin, X. (2019) · ACM Computing Surveys · doi:10.1145/3292674 · Cited by 423
Metadata
- Authors
- Razzaque, M. A., Milojevic-Jevric, M., Palade, A., & Clarke, S.
- Venue
- IEEE Internet of Things Journal
- Published
- 2016-02
- Volume
- 3
- Issue
- 1
- Pages
- 70-95
- ISSN
- 2327-4662 (ISSN-L)
- OpenAlex
- W2241118198
- Cited by
- 1,024
- References
- 2
- FWCI
- 124.33
- Type
- journal article
- Language
- en
- Open access
- green
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