IoT Frameworks Performance Optimization Utilizing Rank-Based Fog Orchestration

The rapid expansion of Internet of Things (IoT) devices and their growing complexity demand continuous advancements in system performance, particularly in accuracy, and speed. This paper presents the novel Rank-Based Fog Orchestration (RBFO) framework to achieve better performance by optimizing resource allocation, and service provisioning. The RBFO framework integrates innovative solutions, including an Orchestrator nodes layer, and the RankBased Service Provisioning (RBSP) and IoT Resource Utilization (IRU) algorithms. These components facilitate efficient service ranking, task scheduling, and load balancing across IoT, fog, and cloud layers, reducing data packet errors and minimizing latency. Performance metrics, such as Deadline Miss Ratio (DMR), speedup ratio, and packet error ratio demonstrate the framework's effectiveness. Simulation results highlight substantial improvements, with the RBFO framework achieving an average latency reduction of 23.5 % and a 30 % decrease in packet error rates compared to existing decentralized models. These results underline its capacity to handle resource-intensive and time-sensitive IoT applications. By achieving significant improvements over centralized and decentralized frameworks, the RBFO framework establishes itself as a robust and scalable solution for the evolving needs of IoT-fog-cloud computing systems. The significance of this research lies in the ability of the proposed RBFO framework to surpass the performance of recent existing frameworks in accuracy and latency reduction which makes it a significant leap in the modern computing paradigms. This improvement has a positive impact on all real-life applications that depend on IoT-Fog-Cloud computing such as healthcare sectors, automated factories, and smart cities.