Enhancing Quality of Service (QoS) and minimizing application placement delay in cloud-fog nodes through meta-heuristic algorithms

Abstract

Efficient module placement in Cloud-Fog computing enhances QoS and minimizes delay. Binary Particle Swarm Optimization (BPSO) and Binary Bat Algorithm (BBA), effective meta-heuristic algorithms, address dynamic fog complexities. This study models placement as binary optimization, incorporating resource availability and latency. BPSO and BBA optimize module placement, demonstrated through simulations improving response time, throughput, and resource utilization. These meta-heuristic methods surpass traditional techniques, optimizing cloud-fog systems, achieving superior QoS, and reduced delay.