Research Area:  Internet of Things
The Internet of Things (IoT) has been growing over the past few years due to its flexibility and ease of use in real-time applications. The IoTs foremost task is ensuring that there is proper communication between different types of applications and devices, and that the application layer protocols fulfill this necessity. However, as the number of applications grows, it is necessary to modify or enhance the application layer protocols according to specific IoT applications, allowing specific issues to be addressed, such as dynamic adaption to network conditions and interoperability. Recently, several IoT application layer protocols have been enhanced and modified according to application requirements. However, no existing survey articles have focused on these protocols. In this article, we survey traditional and recent advances in IoT application layer protocols, as well as relevant real-time applications and their adapted application layer protocols for improving performance. As changing the nature of protocols for each application is unrealistic, machine learning offers means of making protocols intelligent and able to adapt dynamically. In this context, we focus on providing open challenges to drive IoT application layer protocols in such a direction.
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Author(s) Name:  Praveen Kumar Donta,Satish Narayana Srirama,Tarachand Amgoth,Chandra Sekhara Rao Annavarapu
Journal name:  Digital Communications and Networks
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Publisher name:  Elsevier
DOI:  10.1016/j.dcan.2021.10.004
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Paper Link:   https://www.sciencedirect.com/science/article/pii/S2352864821000845