Greedy-Genetic Algorithm Based Video Data Scheduling Over 5G Networks

Essential components in wireless systems are schedulin and resource allocation. The problems scheduling refers to inactive users a given time slot terms of allocation it the issues physical layer resources such as power bandwidth among active users. In Long Time Evolution (LTE) downlink optimized problem flow deadlines that incorporate formulation surveyed algorithm for achieving enhanced performance levels. major challenges appear areas quality constrains video processing sectors 5G. proposed work focuses on through new radio (NR) scheduler. Initially, Priority Technique based greedy genetic is offering better QOS reduced durations. Moreover, used both Optimizing individual steps finding out optimal solutions resolving entire problem. Genetic Algorithm identified by means relying selection attributes. Finally, proves be efficient after execution series experiments.