Hybrid Particle Swarm Optimization with Firefly based Resource Provisioning Technique for Data Fusion Fog-Cloud Computing Platforms
Joseph B. Awotunde1’*, Hrudaya K. Tripathy2, Anjan Bandyopadhyay3
1 Faculty of Information and Communication Sciences, University of Ilorin, Nigeria
2 School of Computer Engineering, Kalinga Institute of Industrial Technology, India
3 Kalinga Institute of Industrial Technology (KIIIT) Bhubaneswar, Odisha, India
Emails: awotunde.jb@unilorin.edu.ng; hktripathyfcs@kiit.ac.in; anjan.bandyopadhyayfcs@kiit.ac.in
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.
Keywords: Resource provisioning; Fog computing; Cloud computing; Hybrid metaheuristics; Data Fusion