Advanced Deadlock Detection and Resolution in Distributed File Systems Using AI and Daemon Processes

In distributed file systems (DFS), deadlocks present significant challenges that adversely affect both performance and reliability. Conventional methods for deadlock detection and resolution are typically resource-intensive, time-consuming, and often fail to provide timely solutions. This paper introduces an innovative approach that leverages the synergy of daemon processes and artificial intelligence (AI) to enhance deadlock detection and resolution mechanisms. Our proposed method deploys autonomous daemon processes to continuously monitor the system states, providing real-time insights into the operating environment. Additionally, we employ advanced AI algorithms to analyze these states, predict potential deadlocks, and proactively implement resolution strategies before system performance is compromised. Experimental results from our comprehensive testing reveal notable improvements in overall system performance, a significant reduction in deadlock occurrences, and enhanced reliability. These findings affirm the efficacy of the proposed approach and its potential to revolutionize deadlock management in distributed file systems, paving the way for more robust and efficient computing environments.