A Multi-Objective Scheduling Algorithm for Cloud Environments: Optimizing QoS Under Deadlines, Priorities, and Fault Tolerance

This paper addresses the growing need for intelligent, adaptive scheduling algorithms in cloud computing environments. Existing approaches often fail to account for real-world constraints such as deadlines, task priorities, and fault tolerance while also optimizing multiple conflicting Quality of Service (QoS) parameters. We propose a novel NSGA-II-based multi-objective scheduling framework that aims to optimize time, cost, energy, reliability, and response time concurrently. The algorithm is enhanced with constraint-handling mechanisms and is evaluated through simulation and real-world validation.