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Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications
Open accessAbstract
This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling technologies, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling technologies, protocols, and applications. Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant protocols and application issues to enable researchers and application developers to get up to speed quickly on how the different protocols fit together to deliver desired functionalities without having to go through RFCs and the standards specifications. We also provide an overview of some of the key IoT challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and other emerging technologies including big data analytics and cloud and fog computing. We also present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different protocols presented in the paper fit together to deliver desired IoT services.
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“The growth of the Industrial Internet of Things (IIoT) is leading to more industrial devices like sensors, instruments, controllers, and appliances being connected and becoming IP-enabled [24].”
From Seamless Industry 4.0 Integration: A Multilayered Cyber-Security Framework for Resilient SCADA Deployments in CPPS (2023) · cites this paper as [24]
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“TLMs are widely integrated into edge computing [140] and IoT environments [141], allowing devices to process and interpret natural language commands locally, without reliance on cloud infrastructure.”
From Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions (2025) · cites this paper as [141]
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Satamraju, K. P., & Malarkodi, B. (2020) · Sensors · doi:10.3390/s20051389 · Cited by 115
Ogbodo, E. U., Abu-Mahfouz, A. M. I., & Kurien, A. M. (2022) · Sensors · doi:10.3390/s22166313 · Cited by 109
“[1] 5G: √ , LPWAN: √ x x x QoS: √ , QoE: x x x X [3] 5G: x, LPWAN: x x x x QoS: √ , QoE: x x x X [4] 5G: x, LPWAN: x x x x QoS: x, QoE; x x x X [5] 5G: x, LPWAN: √ x x x QoS: √ , QoE; x √ x X [8] 5G: √ , LPWAN: √ x x x QoS: √ , QoE; x √ x X [9] 5G: √ , LPWAN: √ x x x QoS: x, QoE; x √ x X [10] 5G: √ , LPWAN: √ x x x Qo…”
MethodA Comprehensive Study on LPWANs With a Focus on the Potential of LoRa/LoRaWAN Systems
Milarokostas, C., Tsolkas, D., Passas, N. I., & Merakos, L. F. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3229846 · Cited by 116
“context, the Internet of Things (IoT) technology [2] serves as a key enabler for the realization of the mMTC scenario.”
BackgroundUllah, I., Adhikari, D., Su, X., Palmieri, F., Wu, C., & Choi, C. (2024) · Digital Communications and Networks · doi:10.1016/j.dcan.2024.02.007 · Cited by 111
Babar, M. A., & Arif, F. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.07.029 · Cited by 108
Analyzing challenges to Internet of Things (IoT) adoption and diffusion: An Indian context
Luthra, S., Garg, D., Mangla, S. K., & Berwal, Y. P. S. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2017.12.094 · Cited by 108
Toward Efficient Service Composition Techniques in the Internet of Things
Hamzei, M., & Navimipour, N. J. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2861742 · Cited by 108
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Certificate-Based Anonymous Device Access Control Scheme for IoT Environment
Malani, S., Jangirala, S., Das, A. K., Srinathan, K., & Jo, M. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2931372 · Cited by 107
Softwarization of Internet of Things Infrastructure for Secure and Smart Healthcare
Salahuddin, M. A., Al-Fuqaha, A., Guizani, M., Shuaib, K., & Sallabi, F. (2017) · Computer · doi:10.1109/mc.2017.195 · Cited by 148
Self-citationA Deep Learning-Based Intelligent Medicine Recognition System for Chronic Patients
Chang, W., Chen, L.-B., Hsu, C.-H., Lin, C., & Yang, T.-C. (2019) · IEEE Access · doi:10.1109/access.2019.2908843 · Cited by 107
Imran, I., Ghaffar, Z., Alshahrani, A. S., Fayaz, M., Alghamdi, A. M., & Gwak, J. (2021) · Electronics · doi:10.3390/electronics10080880 · Cited by 112
“In the literature, several surveys have tackled different IoT challenges and aspects including IoT applications, challenges, and opportunities [6], IoT frameworks, IoT security [7–9], IoT standardization [10], application of in software-defined networking (SDN) in IoT [11], IoT and cloud integration [12].”
BackgroundIoT Service Slicing and Task Offloading for Edge Computing
Hwang, J.-Y., Nkenyereye, L., Sung, N.-M., Kim, J., & Song, J. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3052498 · Cited by 109
Access Control for IoT: A Survey of Existing Research, Dynamic Policies and Future Directions
Ragothaman, K. N. M., Wang, Y., Rimal, B. P., & Lawrence, M. (2023) · Sensors · doi:10.3390/s23041805 · Cited by 107
“Scalability: Scalability is the ability for any access control process to continue to function properly when the number of users and devices changes [24].”
BackgroundIoT reliability: a review leading to 5 key research directions
Moore, S. J., Nugent, C. D., Zhang, S., & Cleland, I. (2020) · CCF Transactions on Pervasive Computing and Interaction · doi:10.1007/s42486-020-00037-z · Cited by 106
Distributed and Adaptive Medium Access Control for Internet-of-Things-Enabled Mobile Networks
Ye, Q. J., & Zhuang, W. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2566659 · Cited by 106
CrowdSenSim: a Simulation Platform for Mobile Crowdsensing in Realistic Urban Environments
Fiandrino, C., Capponi, A., Cacciatore, G., Dzmitry Kliazovich, A., Sorger, U., Bouvry, P., Kantarcı, B., Granelli, F., & Giordano, S. (2017) · IEEE Access · doi:10.1109/access.2017.2671678 · Cited by 106
Elsaadany, M., Ali, A., & Hamouda, W. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2728013 · Cited by 105
Metadata
- Authors
- Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M.
- Affiliations
- Qatar University (QA)
- Western Michigan University (US)
- Chicago State University (US)
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2015
- Volume
- 17
- Issue
- 4
- Pages
- 2347-2376
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W2134295053
- Cited by
- 8,630
- References
- 165
- Citations by year
- 2026: 599 · 2025: 718 · 2024: 703 · 2023: 807 · 2022: 805 · 2021: 995 · 2020: 1145 · 2019: 1055 · 2018: 945 · 2017: 607 · 2016: 238 · 2015: 13
- FWCI
- 687.33
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- Qatar University QSpace (Qatar University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT Networks and Protocols
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- Internet of Things, IoT protocols, RFID, smart sensors, machine-to-machine communication, enabling technologies, IoT applications, big data analytics, cloud computing, fog computing, intelligent decision-making
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