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Creating Collision-Free Communication in IoT with 6G Using Multiple Machine Access Learning Collision Avoidance Protocol

Shakeel, P. Mohamed ; Baskar, S. ; Fouad, Hassan ; Manogaran, Gunasekaran ; Saravanan, Vijayalakshmi ; Xin, Qin

Mobile networks and applications, 2021-06, Vol.26 (3), p.969-980 [Periódico revisado por pares]

New York: Springer US

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Título:
Creating Collision-Free Communication in IoT with 6G Using Multiple Machine Access Learning Collision Avoidance Protocol
Autor: Shakeel, P. Mohamed ; Baskar, S. ; Fouad, Hassan ; Manogaran, Gunasekaran ; Saravanan, Vijayalakshmi ; Xin, Qin
Assuntos: 6G mobile communication ; Access control ; Cloud computing ; Collision avoidance ; Collision dynamics ; Communication ; Communication networks ; Communications Engineering ; Computer Communication Networks ; Edge computing ; Elastic scattering ; Electrical Engineering ; Engineering ; Internet of Things ; IT in Business ; Learning ; Network latency ; Networks ; Resource utilization ; Statistical analysis ; Terahertz frequencies ; Wireless communications ; Wireless networks
É parte de: Mobile networks and applications, 2021-06, Vol.26 (3), p.969-980
Descrição: Cloud computing is an important technology to offer consumer appliances a wide pool of elastic resources. The heterogeneous network faces collision while making communication, which reduces the entire network performance. The future cloud-edge networks will deal with a vast amount of clients and servers, such as the Internet of Things (IoT) and the 6G networks, which require flexible solutions. From these points, Multiple Machine Access Learning with Collision Carrier Avoidance (MMALCCA) protocol is proposed in the environment of 6G Internet of Things for creating an effective communication process. This protocol employs the Media Access Control (MAC) protocol for the sync of high-speed wireless communication networks in the Terahertz (THz) band. MMALCCA performs multiple machine access and collision control for improving the resource utilization and latency-less services of the users. The decisions of the protocol are made using the output of the classification and regression learning method for improving the efficiency of MAC sync. The performance of the proposed protocol is verified using the metrics latency, collision probability, service failure, and resource utilization by varying channels and user equipment density.
Editor: New York: Springer US
Idioma: Inglês

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Creating Collision-Free Communication in IoT with 6G Using Multiple Machine Access Learning Collision Avoidance Protocol

Shakeel, P. Mohamed ; Baskar, S. ; Fouad, Hassan ; Manogaran, Gunasekaran ; Saravanan, Vijayalakshmi ; Xin, Qin

New York: Springer US

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