Effective Resource Utilization in Hadoop Using Ganglia

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dc.contributor.authorSrungarapati, B.
dc.contributor.authorPamarthi, M.
dc.contributor.authorVakada, V.
dc.contributor.authorHegde, A.
dc.contributor.authorBhowmik, B.
dc.date.accessioned2026-02-06T06:34:20Z
dc.date.issued2024
dc.description.abstractThe exponential growth of big data has led to the widespread adoption of Hadoop clusters for storing and processing large volumes of data. Efficient management of resources within these clusters is crucial for achieving optimal performance and cost efficiency. This research paper explores the use of Hadoop and Ganglia for monitoring and optimizing resource utilization in Hadoop clusters. The study demonstrates that leveraging Hadoop and Ganglia is an effective strategy for improving cluster performance and resource efficiency. Results show significant enhancements in cluster performance and resource utilization, highlighting the importance of proactive resource management in Hadoop environments. © 2024 IEEE.
dc.identifier.citation3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024, 2024, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/CCIS63231.2024.10932012
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/29193
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectBig Data
dc.subjectGanglia Monitoring
dc.subjectHadoop cluster
dc.subjectHadoop Distributed File System
dc.subjectResource Management
dc.titleEffective Resource Utilization in Hadoop Using Ganglia

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