AI Task Scheduling in Distributed Cloud Environments: Improving Resource-Intensive Application QoS
Keywords:
Intelligent task scheduling, AI, distributed cloud environmentsAbstract
Task scheduling is needed for resource-intensive cloud computing applications that are growing fast. These apps use a lot of CPU, making QoS crucial. AI-driven work scheduling may minimize delays, optimise resource allocation, and improve application performance. AI task scheduling may enhance resource-intensive application QoS in distributed cloud settings. Machine, deep, and reinforcement learning are used to schedule cloud infrastructure jobs. Scalability, latency, and processing overhead are addressed in AI-based job scheduling. Reports recommend hybrid AI-driven scheduling systems that blend conventional and AI methodologies for efficiency. We demonstrate how AI-based job scheduling enhances cloud QoS and resource usage using several methods.
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