Fog computing-based beam allocation and co-operative task distribution model for green 5G mobile network

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Bibliografiset tiedot
Julkaisussa:Innovations in Systems and Software Engineering vol. 20, no. 4 (Dec 2024), p. 869
Päätekijä: Deb, Priti
Muut tekijät: De, Debashis
Julkaistu:
Springer Nature B.V.
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100 1 |a Deb, Priti  |u Maulana Abul Kalam Azad University of Technology, West Bengal, Centre of Mobile Cloud Computing, Department of Computer Science and Engineering, Simhat, Nadia, India (GRID:grid.440742.1) (ISNI:0000 0004 1799 6713); Institute of Engineering and Management, Kolkata, MCA Department Management House, Kolkata, India (GRID:grid.464589.2) 
245 1 |a Fog computing-based beam allocation and co-operative task distribution model for green 5G mobile network 
260 |b Springer Nature B.V.  |c Dec 2024 
513 |a Journal Article 
520 3 |a The communication and computation world is being gone through a lack of proper power consumption models in multi-tier small cell-based heterogeneous networks. Efficient spectrum utilization with proper task distribution is an emerging criterion for 5G-based wireless communication. Delay incurred by task offloading degrades the quality of services (QoS). To reduce power consumption, delay, and increase spectral efficiency, fog-based power-efficient beam allocation and task distribution model for IoT network are proposed. Femtolet acts as a base station and performs also computational assignments like a cloudlet. Hence, femtolet can act as a fog device. Femtolet allocates beam to each IoT device based on maximum spectral efficiency. Secondly, the task distribution is performed. If the femtolet itself can perform tasks, it processes them and sends back to the IoT device. The global femtolet concept appears when two or more femtolets are needed to perform tasks. The connection between IoT devices (IoTD) and femtolet is done by 5G beamforming. Mixed integer linear programming is formulated. Power consumption, delay, and spectral efficiency are the QoS factors of the IoT network. The simulation result demonstrates that proposed architecture decreases power consumption and delay by 23–47% and 15–25%, respectively, than cloud-sensitive approaches. The proposed approach enhances spectral efficiency and SINR by 12–15% and 15–25%, respectively. The comparative analysis with existing approaches shows that this model is novel, green, and fast. 
653 |a Scheduling 
653 |a Linear programming 
653 |a Internet of Things 
653 |a Wireless communications 
653 |a Beamforming 
653 |a Edge computing 
653 |a Integer programming 
653 |a Delay 
653 |a Communication 
653 |a 5G mobile communication 
653 |a Quality of service architectures 
653 |a Optimization 
653 |a Computation offloading 
653 |a Power management 
653 |a Quality of service 
653 |a Spectrum allocation 
653 |a Mixed integer 
653 |a Cloud computing 
653 |a Power consumption 
653 |a Efficiency 
700 1 |a De, Debashis  |u Maulana Abul Kalam Azad University of Technology, West Bengal, Centre of Mobile Cloud Computing, Department of Computer Science and Engineering, Simhat, Nadia, India (GRID:grid.440742.1) (ISNI:0000 0004 1799 6713); University of Western Australia, Department of Physics, Crawley, Australia (GRID:grid.1012.2) (ISNI:0000 0004 1936 7910) 
773 0 |t Innovations in Systems and Software Engineering  |g vol. 20, no. 4 (Dec 2024), p. 869 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3254724242/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
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