Analysis of Fog Node Task Scheduling Methods for Optimization of Resource Allocation
Neha Sharma, Deepti Sharma · 2025
Real-time interactive services are essential in the Internet of Things (IoT) age, yet cloud computing can result in latency and network congestion. The concept of fog computing (FC) is examined in this work along with its features, applications, planning, and task scheduling (TS) techniques based on deterministic-based fog strategies, machine learning (ML), metaheuristics, and heuristics. This study examines fog computing's characteristics, use, architecture, and task scheduling techniques that use machine learning, deterministic algorithms, heuristics, and metaheuristics. Also, discuss the challenges and issues that exist in fog computing. By reducing latency, increasing efficiency, and moving processing closer to the network's edge, FC seeks to address these issues. Fog computing presents a viable way to enable real-time interactive services in the Internet of Things age by allocating resources and processing power closer to the location of data generation. FC is a decentralized architecture that boosts productivity and maximizes network resources. This cloud-based job offloading lowers bandwidth utilization, boosts speed, and improves real-time interactive services in IoT applications.