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This document presents a thesis on leveraging hybrid models for resource allocation and prediction in dynamic edge computing environments. It discusses the integration of machine learning and heuristic methods to improve resource management, particularly in latency-sensitive applications. The research highlights the effectiveness of hybrid prediction frameworks in optimizing resource utilization and addresses the challenges posed by the dynamic nature of edge computing.
- Author
- printworkhp
- Language
- EN