Hybrid multi objective marine predators algorithm based clustering for lightweight resource scheduling and application placement in fog DOI Creative Commons

Rajoo Baskar,

E. Mohanraj

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 7, 2025

The Internet of Things (IoT) has boosted fog computing, which complements the cloud. This is critical for applications that need close user proximity. Efficient allocation IoT to fog, as well device scheduling, enabling realistic execution application deployment in environment. scheduling difficulties are multi-objective nature, since they must handle issues avoiding resource waste, network latency, and maximising Quality Service (QoS) on nodes. In this research, Hybrid Multi-Objective Marine Predators Algorithm-based Clustering Fog Picker (HMMPACFP) Technique developed a combinatorial model tackling problem node allocation, with goal achieving dynamic using lightweight characteristics. Utilised allocate components nodes based QoS parameters. Simulation trials proposed HMMPACFP scheme utilising iMetal iFogSim Hypervolume (HV) Generational Distance (IGD) demonstrated its superiority over benchmarked methodologies utilised evaluation. combination suggested resulted 32.18% faster convergence, 26.92% more solution variety, better balance between exploration exploitation rates.

Language: Английский

A refined Greylag Goose optimization method for effective IoT service allocation in edge computing systems DOI Creative Commons

Hossein Najafi Khosrowshahi,

Hadi S. Aghdasi, Pedram Salehpour

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 6, 2025

Language: Английский

Citations

0
Hybrid multi objective marine predators algorithm based clustering for lightweight resource scheduling and application placement in fog DOI Creative Commons

Rajoo Baskar,

E. Mohanraj

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 7, 2025

The Internet of Things (IoT) has boosted fog computing, which complements the cloud. This is critical for applications that need close user proximity. Efficient allocation IoT to fog, as well device scheduling, enabling realistic execution application deployment in environment. scheduling difficulties are multi-objective nature, since they must handle issues avoiding resource waste, network latency, and maximising Quality Service (QoS) on nodes. In this research, Hybrid Multi-Objective Marine Predators Algorithm-based Clustering Fog Picker (HMMPACFP) Technique developed a combinatorial model tackling problem node allocation, with goal achieving dynamic using lightweight characteristics. Utilised allocate components nodes based QoS parameters. Simulation trials proposed HMMPACFP scheme utilising iMetal iFogSim Hypervolume (HV) Generational Distance (IGD) demonstrated its superiority over benchmarked methodologies utilised evaluation. combination suggested resulted 32.18% faster convergence, 26.92% more solution variety, better balance between exploration exploitation rates.

Language: Английский

Citations

0