ISSN No:2250-3676 ----- Crossref DOI Prefix: 10.64771 ----- Impact Factor: 9.625
(Peer Reviewed, Referred & Indexed Journal)
Dynamic Workload Optimization In Enterprise Data Platforms Through Adaptive Data PipelinesID: 2852 Abstract :This Paper Introduces A Framework For Building Data Pipelines That Adapt At Runtime To Shifting Workload Patterns In Enterprise Environments. The System Redistributes Compute And Memory Resources Without Manual Intervention By Instrumenting Pipeline Stages With Feedback Loops And Cost-based Decision Heuristics. Evaluations On Large-scale ELT Workflows Demonstrate Significant Reductions In Latency And Operational Cost Under Variable Load Conditions. |
Published:24-4-2022 Issue:Vol. 22 No. 4 (2022) Page Nos:17-24 Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to CiteSunil Kumar Mudusu, Dynamic Workload Optimization in Enterprise Data Platforms through Adaptive Data Pipelines , 2022, International Journal of Engineering Sciences and Advanced Technology, 22(4), Page 17-24, ISSN No: 2250-3676. |