Task scheduling in cloud computing

In the realm of cloud computing, efficient task scheduling is paramount for optimal resource utilization and timely task completion. This project presents a comprehensive task scheduling system designed to manage computational tasks in a cloud computing environment. The system comprises four key modules: Task Management, Node Management, Scheduler, and User Interface. The Task Management module handles task submissions, maintains a task queue, and assigns tasks to available computational nodes. It ensures equitable distribution of tasks and manages task priorities based on user specifications. The Node Management module monitors the status of computational nodes, allocates resources for task execution, and optimizes node utilization. The Scheduler module orchestrates the scheduling process by evaluating task and node statuses, assignments based on node availability and workload distribution. The User Interface module provides a user-friendly interface for task submission, monitoring, and reporting. Users can submit tasks, track task progress, receive real-time updates on task status, and access historical task data for analysis. The proposed system offers several advantages, including improved resource utilization, reduced task completion time, and enhanced user experience. By leveraging efficient task scheduling algorithms and intuitive user interfaces, the system empowers cloud computing environments to effectively manage computational tasks and meet user requirements.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-02
DOI
https://doi.org/10.5281/zenodo.15576027
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Task scheduling in cloud computing

Zenodo (CERN European Organization for Nuclear Research)
Cloud Computing and Resource Management
article

Task scheduling in cloud computing

article en

Abstract

In the realm of cloud computing, efficient task scheduling is paramount for optimal resource utilization and timely task completion. This project presents a comprehensive task scheduling system designed to manage computational tasks in a cloud computing environment. The system comprises four key modules: Task Management, Node Management, Scheduler, and User Interface. The Task Management module handles task submissions, maintains a task queue, and assigns tasks to available computational nodes. It ensures equitable distribution of tasks and manages task priorities based on user specifications. The Node Management module monitors the status of computational nodes, allocates resources for task execution, and optimizes node utilization. The Scheduler module orchestrates the scheduling process by evaluating task and node statuses, assignments based on node availability and workload distribution. The User Interface module provides a user-friendly interface for task submission, monitoring, and reporting. Users can submit tasks, track task progress, receive real-time updates on task status, and access historical task data for analysis. The proposed system offers several advantages, including improved resource utilization, reduced task completion time, and enhanced user experience. By leveraging efficient task scheduling algorithms and intuitive user interfaces, the system empowers cloud computing environments to effectively manage computational tasks and meet user requirements.

Zenodo (CERN European Organization for Nuclear Research)
Vels University (IN)
Openalex Percentile: Top 45%
Cloud Computing and Resource Management
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