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Title	Hybrid Particle Swarm Optimization With Firefly Based Resource Provisioning Technique For Data Fusion Fog-Cloud Computing Platforms
ID_Doc	29804
Authors	Awotunde J.B.; Tripathy H.K.; Bandyopadhyay A.
Year	2022
Published	Fusion: Practice and Applications, 8, 2
DOI	http://dx.doi.org/10.54216/FPA.080203
Abstract	The recent wide acceptance of cloud and virtualization technologies has made a number of Internet of Things (IoT) applications practical. Although these technologies are typically useful, they may introduce a high transmission latency in IoT environments, e.g., data fusion in smart cities. To address this issue, fog computing, a distributed decentralized computing layer between IoT hardware and the cloud layer, can be used. To facilitate the use of fog computing in IoT data fusion environments, this paper proposes a new Hybrid Particle Swarm Optimization with Firefly based Resource Provisioning Technique (HPSOFF-RPT) model for fog-cloud computing platforms. The HPSOFF-RPT model is designed to optimize resource allocation and distribution in IoT environments. The model uses the PSO and FF algorithms to provision resources in the fog-cloud environment. To evaluate performance, a wide-ranging simulation analysis is performed. The simulation results show that the proposed model improves performance compared to the existing optimization algorithms. © 2022, American Scientific Publishing Group (ASPG). All rights reserved.
Author Keywords	Cloud computing; Data Fusion; Fog computing; Hybrid metaheuristics; Resource provisioning

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