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Title Opportunistic Resource Allocation For Narrowband Internet Of Things: A Literature Review
ID_Doc 40241
Authors Muteba K.F.; Djouani K.; Olwal T.O.
Year 2020
Published 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020
DOI http://dx.doi.org/10.1109/ICECCE49384.2020.9179427
Abstract Nowadays, the growing adoption of the Internet of Things (IoT) is reshaping the telecommunication landscape and has penetrated every aspect of our lives with influential applications on smart health, home automation, smart logistics, smart industries and smart cities. These advanced technologies bring about numerous benefits and has begun to play a major role in daily lives, particularly data mining applied in precision agriculture to discover knowledge. Also in agro-industrial production chain, the combination of wireless and distributed specific sensor devices with the simulation of climatic conditions in order to track the evolution of grapes for wineries is outstanding. Mobile IoT such as narrowband-IoT (NB-IoT) and the long-term evolution (LTE) for machines (LTE-M) are significant innovations of this accelerating development of IoT technologies. In the era of ubiquitous communication where everything is connected to the internet, NB-IoT systems are expected to offer better quality-of-services (QoS) to end users than the traditional IoT paradigm. However, offering better QoS satisfaction to end users will become a great challenge due to the bottleneck caused by the dual problem of increasing IoT use cases and the shortage of wireless spectrum resources. Whilst discussing the recent innovative solutions of NB-IoT resource allocation, significant challenges and open issues related to the real-time implementation of NB-IoT are identified and discussed. Therefore, this paper gives a general overview of the resource allocation solutions in this NB-IoT innovation and further suggests and motivates for the intelligentization of future resource allocation solutions (i.e., the use of artificial intelligence (AI) strategies). © 2020 IEEE.
Author Keywords Artificial intelligence; Intelligentization; Internet of Things; Long-term evolution; Machine learning; Narrowband-IoT; Resource allocation


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