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An Efficient Container Scheduling framework for Resource Allocation in a Cloud Computing Environments

by Shubham Sharma, Ramesh Vishwakarma
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Communications on Applied Electronics
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 40
Year of Publication: 2025
Authors: Shubham Sharma, Ramesh Vishwakarma
10.5120/cae2025652909

Shubham Sharma, Ramesh Vishwakarma . An Efficient Container Scheduling framework for Resource Allocation in a Cloud Computing Environments. Communications on Applied Electronics. 7, 40 ( Jul 2025), 39-48. DOI=10.5120/cae2025652909

@article{ 10.5120/cae2025652909,
author = { Shubham Sharma, Ramesh Vishwakarma },
title = { An Efficient Container Scheduling framework for Resource Allocation in a Cloud Computing Environments },
journal = { Communications on Applied Electronics },
issue_date = { Jul 2025 },
volume = { 7 },
number = { 40 },
month = { Jul },
year = { 2025 },
issn = { 2394-4714 },
pages = { 39-48 },
numpages = {9},
url = { https://www.caeaccess.org/archives/volume7/number40/an-efficient-container-scheduling-framework-for-resource-allocation-in-a-cloud-computing-environments/ },
doi = { 10.5120/cae2025652909 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-07-26T02:32:31.376035+05:30
%A Shubham Sharma
%A Ramesh Vishwakarma
%T An Efficient Container Scheduling framework for Resource Allocation in a Cloud Computing Environments
%J Communications on Applied Electronics
%@ 2394-4714
%V 7
%N 40
%P 39-48
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The rapid evolution of cloud computing has underscored the need for scalable and efficient container orchestration. As organizations increasingly adopt containerized applications to achieve agility and portability, the optimization of container scheduling becomes critical for resource utilization, service reliability, and cost efficiency. This research presents an intelligent container scheduling strategy tailored for cloud environments, integrating resource-aware algorithms and real-time performance metrics to allocate containers dynamically. The proposed approach reduces idle resource fragmentation, balances workload across heterogeneous nodes, and adapts to failures through fault-tolerant mechanisms. Experimental analysis using Docker Swarm demonstrates significant improvement in throughput, reduced latency, and enhanced fault recovery compared to traditional scheduling models. The findings highlight the importance of adaptive, context-aware scheduling policies in advancing cloud-native infrastructure efficiency.

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Index Terms

Computer Science
Information Sciences

Keywords

Container Scheduling Cloud Computing Resource Allocation Docker Swarm Fault Tolerance Load Balancing Container Orchestration Scheduling Algorithm Cloud-Native Applications Resource Optimization

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