id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-953	Aihtesham Kazi	Design of an Iterative Method for MapReduce Scheduling Using Deep Reinforcement Learning and Anomaly Detection	2024	22	.pdf	application/pdf	8260	324	28	Recent advances in machine learning and data analytics have opened new avenues to enhance the adaptability and efficiency of job scheduling in distributed systems. In response to these challenges, this paper contributes a robust scheduling framework specifically designed for MapReduce environments, which integrates advanced machine learning techniques to enhance the adaptability and efficiency of job scheduling.	cache/cana-953.pdf	txt/cana-953.txt