Abstract
Task scheduling plays a crucial role in optimizing resource utilization and enhancing performance in cloud computing
environments. Efficient scheduling algorithms help manage workloads, minimize execution time, balance resource allocation,
and ensure Quality of Service (QoS) compliance. This paper provides a comprehensive study aboubt task scheduling techniques,
various applications of cloud task scheduling, ranging from big data processing to IoT integration and high-performance
computing. Furthermore, we analyze widely used scheduling tools such as CloudSim, iFogSim, and WorkflowSim. Performance
evaluation metrics, including makespan, load balancing, and energy efficiency, are discussed to highlight key factors influencing
scheduling decisions. Finally, we outline current research challenges and future directions, emphasizing the need for adaptive
and intelligent scheduling mechanisms to enhance cloud computing efficiency
Keywords
Task Scheduling
Cloud Computing
Resource Allocation
Heuristic and Metaheuristic Algorithms
AI-based Scheduling
Performance Optimization
Load Balancing
QoS-Aware Scheduling
Authors
How to Cite this Article
T.Arunprakasam, Dr.M.Gunasekaran (2015).
"TASK SCHEDULING IN CLOUD COMPUTING: CHALLENGES, APPLICATIONS, TOOLS, AND PERFORMANCE METRICS".
International Journal of Contemporary Research in Computer Science and Technology,
1(9), pp. 375-382.
