DEVELOP AND ANALYZE DYNAMIC HEALTH-BASED ELECTION ALGORITHM FOR ROLE PROMOTION IN HADOOP HDFS

The Hadoop Distributed File System (HDFS) is a key part of scalable data storage. However, standard methods for choosing Active and Standby NameNodes roles often rely on static configurations or close supervision by hand, which makes fault recovery and load balancing harder. This study solves the problem of these methods not working well by creating and studying a dynamic, health-based voting algorithm for smart job promotion in Hadoop HDFS. The objective of the work is to make a system that can change and select the best node for promotion based on the health of resources at any given time. Using normalized values of CPU usage, RAM availability, network bandwidth, and uptime, the proposed method creates a composite health score. Each node is then ranked based on its final score. In the study the finding demonstrate that the DataNode DN1 got the best score of 0.7655, beating out DN2 (0.1189) and DN3 (0.6), so it was promoted to Active NameNode. This finding proves that the algorithm can choose the most stable node on the fly, which lessens the effects of a split and makes the system more resilient. The results show that our smart voting method greatly enhances fault tolerance and cluster performance by making sure that the best roles are assigned when node conditions change.