A Hyper-Active Approach to Parallel Load Distribution for Optimal Cloud Throughput

Author(s)	Ms. V.Anantha Lakshmi
Country	India
Abstract	Additionally, it was unable to estimate the dynamic workload, resulting in uneven resource utilization and potential service delays. These issues are addressed by developing the Hyper-Active Approach to Parallel Load Distribution (HAPLD), which dynamically monitors workload patterns, resource availability, and on-demand services without delay. The proposed HAPLD comprises a multi-level parallel scheduling mechanism that combines estimated resource allocation and adaptive task migration to ensure a balanced workload distribution across cloud nodes. The Google Cluster Workload Traces 2019 datasets were collected from the online source Kaggle. Experimental results show that the proposed approach obtains high performance in terms of Response Time (RT), Execution Time (ET), Throughput (TP), Task Migration Rate (TMR), and CPU Utilization (CU).
Keywords	Cloud Service Providers (CSPs), Quality Of Service (QoS), Load balancing, Hyper-Active Approach to Parallel Load Distribution (HAPLD), Multi-Level Parallel Scheduling Mechanism.
Field	Computer Applications
Published In	Volume 16, Issue 4, October-December 2025
Published On	2025-10-09

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