International Journal of Network Management, Journal Year: 2025, Volume and Issue: 35(2)
Published: Feb. 27, 2025
ABSTRACT Rapid growth in intelligent digital media interaction systems (IDMIS) has created new difficulties controlling and optimizing content distribution engagement, especially with the impending 6G networks. The purpose of investigate is to create an system that uses network slicing increase communication user experience through seamless connectivity, dynamic distribution, real‐time engagement. structure includes a dynamic, multilayered architecture for IDMIS, capital allocated based on demand type. machine learning (ML) algorithms predict behavior optimize delivery real time. To correctly behavior, research gathers data capture users' performance preference (historical data, demographics, contextual feedback). Once collected, are processed reduce dimensionality using principal component analysis (PCA). Refined Support Vector Machine Integrated Flying Fox Optimization (RSVM‐FFO) predicts optimizes Metrics used evaluate RSVM‐FFO approach, such as F1‐score (98.12%), accuracy (98.59%), precision (98.57%), recall (98.17%). results reveal suggested considerably improve effectiveness by reducing latency bandwidth usage while providing highly responsive experience. Finally, advancement high‐performance, customized services combination IDMIS slicing.
Language: Английский