Reliability and performance of resource efficiency in dynamic optimization scheduling using multi-agent microservice cloud-fog on IoT applications

In the ever-evolving landscape of technology, both in the Internet of Things (IoT) and of microservice-based cloud-fog with IoT applications, reliability has emerged as a pivotal challenge. This research explores the intricate integration of the IoT with cloud computing through fog computing, addressing critical challenges and presenting an advanced strategy for dynamic task scheduling, reliability, and performance enhancement. It highlights the limitations of current cloud-only architectures in meeting the dynamic requirements of IoT with fog, which demand more efficient data processing and enhanced communication management. Fog and cloud computing are the best options, and an optimal solution is leveraging fog computing’s proximity to IoT devices for reduced latency and cloud computing’s extensive storage and processing capabilities. The paper introduces a novel Dynamic Mayfly optimization Scheduling (DMOS) algorithm based on and designed to minimize energy usage while meeting task deadlines and maintaining system reliability and performance. This algorithm’s effectiveness is validated through simulations on an enhanced CloudSim platform, demonstrating its superiority in energy efficiency and performance reliability over traditional methods. This work contributes significantly to IoT and cloud computing, proposing a dynamic and intelligent approach to task scheduling crucial for IoT systems’ sustainable, reliable, and efficient operation. Through comprehensive experimentation and comparative analysis, we demonstrate the efficacy of our approach in improving reliability, reducing latency, and optimizing resource utilization in Cloud-Fog-based IoT applications. Our findings highlight the potential of dynamic optimization scheduling with multi-agent microservices to significantly enhance the performance and scalability of IoT systems, paving the way for more efficient and reliable IoT deployments in diverse domains.