SYSTEM COST AND RELIABILITY OPTIMIZATION THROUGH FUZZY-BASED TASK SCHEDULING IN DISTRIBUTED COMPUTING SYSTEMS

Soniya Saini; Dr. Sandeep Kumar Tiwari; Dr. Ankur Nehra

doi:10.59828/pijms.v1i3.14

Authors

Soniya Saini Research Scholar, Department of Mathematics, Faculty of Science, Motherhood University, Haridwar, Uttarakhand, 24766, India Author
Dr. Sandeep Kumar Tiwari Supervisor, Department of Mathematics, Faculty of Science, Motherhood University, Roorkee, Uttarakhand, 247667, India Author
Dr. Ankur Nehra Co-supervisor, Department of Mathematics, Dhanauri P.G. College, Dhanauri, Haridwar, Uttarakhand, 247667, India Author

DOI:

https://doi.org/10.59828/pijms.v1i3.14

Abstract

Efficient task scheduling in distributed and cloud-fog computing environments plays a pivotal role in optimizing system performance, reliability, and operational costs. This study presents a comprehensive task scheduling model that integrates cost-aware and reliability-driven strategies to enhance resource utilization while minimizing system downtime and overall execution expense. By incorporating dynamic workload distribution, fuzzy-logic-based decision-making, and hybrid metaheuristic approaches, the proposed model addresses uncertainties and heterogeneity in modern computing systems. Extensive simulations and performance analyses demonstrate that the model achieves significant improvements in system reliability and cost reduction compared to conventional scheduling techniques. The findings offer a practical framework for designing adaptive and efficient scheduling mechanisms in cloud, fog, and IoT-enabled environments.

Keywords: Task Scheduling, System Reliability, Cost Optimization, Cloud Computing, Fog Computing, IoT, Fuzzy Logic, Hybrid Metaheuristics, Resource Allocation.