AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A deep Q‐network–driven intelligent aggregation (DDIA) framework designed to maximize network longevity through self‐learning optimization and the implementation of bitwise‐rotation entanglement entanglement (BRE) for data fusion is proposed.
Resource allocation in the cloud-edges is extremely important to reduce the time of execution, energy usage, and service-level agreement (SLA) breaches when experiencing dynamic workloads. In this paper, the author has proposed an elite co-evolution hybrid optimization model, Hybrid Hierarchical Optimization for Cloud...
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