International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 17, No. 4, 8 Aug. 2025
Cover page and Table of Contents: PDF (size: 1093KB)
STBO: Dynamic Resource-aware Scheduling in Cloud-fog Environments for Improved Task Allocation
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Author(s)
Santhosh Kumar Medishetti
1,*
Karumuri Sri Rama Murthy
2
Venkateshwarlu Kajjam
3
Sudha Singaraju
4
Rameshwaraiah Kurupati
5
Index Terms
Task Scheduling, NP-hard Problem, Cloud-Fog Computing, Virtual Machines, Sewing Training-based Optimization
Abstract
Scheduling is an NP-hard problem, and heuristic algorithms are unable to find approximate solutions within a feasible time frame. Efficient Task Scheduling (TS) in Cloud-Fog Computing (CFC) environments is crucial for meeting the diverse resource demands of modern applications. This paper introduces the Sewing Training-Based Optimization (STBO) algorithm, a novel approach to resource-aware task scheduling that effectively balances workloads across cloud and fog resources. STBO categorizes Virtual Machines (VMs) into low, medium, and high resource utilization queues based on their computational power and availability. By dynamically allocating tasks to these queues, STBO minimizes delays and ensures that tasks with stringent deadlines are executed in optimal environments, enhancing overall system performance. The algorithm leverages processing delays, task deadlines, and VM capabilities to assign tasks intelligently, reducing response times and improving resource utilization. Experimental results demonstrate that STBO outperforms existing scheduling algorithms in reducing makespan by 21.6%, improved energy usage by 31%, and maximizing throughput by 27.8%, making it well-suited for real-time, resource-intensive applications in CFC systems.
Cite This Paper
Santhosh Kumar Medishetti, Karumuri Sri Rama Murthy, Venkateshwarlu Kajjam, Sudha Singaraju, Rameshwaraiah Kurupati, "STBO: Dynamic Resource-aware Scheduling in Cloud-fog Environments for Improved Task Allocation", International Journal of Information Technology and Computer Science(IJITCS), Vol.17, No.4, pp.58-79, 2025. DOI:10.5815/ijitcs.2025.04.06
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