Abstract :

Efficient Job Scheduling Is A Major Challenge In Modern Computing Environments Such As Cloud Computing, Distributed Systems, Parallel And Distributed Processing Systems, And Multicore Architectures. The Increasing Number Of Computational Tasks And Limited Availability Of Shared Resources Often Lead To Execution Conflicts, Resource Contention, And Performance Degradation. Traditional Scheduling Algorithms Mainly Focus On Fairness And Execution Order But Fail To Efficiently Handle Conflicts Among Simultaneously Executing Jobs. To Address This Issue, This Paper Presents A Graph Coloringbased Conflict-aware Job Scheduling Approach Using The DSATUR (Degree Of Saturation) Algorithm. In The Proposed Framework, Jobs Are Modeled As Vertices And Conflicts Between Jobs Are Represented As Edges In A Graph Structure. The Scheduling Problem Is Transformed Into A Graph Coloring Problem Where Each Color Corresponds To A Separate Execution Slot. The DSATUR Algorithm Dynamically Assigns Colors To Vertices While Minimizing Conflicts And Reducing The Total Number Of Execution Slots. Experimental Evaluation Demonstrates That The Proposed Approach Significantly Reduces Makespan, Improves Throughput, And Enhances Resource Utilization Compared To Traditional Scheduling Techniques Such As FCFS And Round Robin. The Proposed Method Is Scalable, Efficient, And Suitable For Largescale Computing Environments Requiring Optimized Conflict-free Scheduling.

Published:

23-6-2026

Issue:

Vol. 26 No. 6 (2026)

Page Nos:

1390-1394

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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