Novel Resource Allocation Approach for Fog Computing-Driven IoT Systems

Authors

  • Purushottam S. Barve, Shweta Saxena, Adars U., N.Venkata Sairam Kumar, Sachin S. Pund, Sheela Upendra

Keywords:

Fog computing (FC), Internet of Things (IoT), resource allocation, energy usage, boosted atom search optimization (BASO)

Abstract

Fog computing (FC) has the potential to lower latency and boost speed. Internet of Things (IoT) networks have difficulties allocating resources efficiently. The approaches used are flexible, scalable, or optimized. To maximize performance indicators, new approaches that utilize real-time information, workload sequences, device accessibility and network circumstances are required. We investigate the allocation of resources and task scheduling for numerous devices in IoT systems in this research. IoT devices must properly choose which data to offload to FC nodes (FCNs) as they acquire enormous amounts of data. To tackle the problem of supporting multiple device connections and facilitating fast data transfers with constrained resources, we suggest executing non-orthogonal multiple access (NOMA). Several devices can simultaneously send data spanning time, frequency and coding domains to an identical FCN because of NOMA. Together, we optimize power transmission and resource assignment for IoT devices, meeting QoS requirements and reducing network energy usage. In this research, a unique boosted atom search optimization (BASO) method is presented to tackle it because it is an NP-hard issue. According to the simulation results, the suggested strategy outperforms in terms of greatest throughput, minimum latency and optimal energy use. 

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References

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Published

26.03.2024

How to Cite

Shweta Saxena, Adars U., N.Venkata Sairam Kumar, Sachin S. Pund, Sheela Upendra, P. S. B. . (2024). Novel Resource Allocation Approach for Fog Computing-Driven IoT Systems. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 1045–1051. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5503

Issue

Vol. 12 No. 21s (2024)

Section

Research Article

License

Copyright (c) 2024 Purushottam S. Barve, Shweta Saxena, Adars U., N.Venkata Sairam Kumar, Sachin S. Pund, Sheela Upendra

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