ISSN Approved Journal || eISSN: 2582-8185 || CODEN: IJSRO2 || Impact Factor 8.2 || Google Scholar and CrossRef Indexed
Fast Publication within 48 hours || Low Article Processing Charges || Peer Reviewed and Referred Journal || Free Certificate
Cloud data centers and networks: Applications and optimization techniques
1 Marketing Programs Advisory Committee. Full Sail University, USA.
2 Department of ECE, KMEA Engineering College, APJ Abdul Kalam Technological University, India.
Research Article
International Journal of Science and Research Archive, 2024, 13(02), 218–226.
Article DOI: 10.30574/ijsra.2024.13.2.2100
Publication history:
Received 23 September 2024; revised on 31 October 2024; accepted on 02 November 2024
Abstract:
As the volume and complexity of big data continue to escalate, optimizing the performance, scalability, and energy efficiency of big data applications within cloud data centers has become increasingly crucial. This journal presents a comprehensive survey of current optimization techniques, focusing on data placement, job scheduling, and network configurations tailored for cloud environments. We explore the impact of various data center topologies on the performance of big data frameworks like Hadoop, emphasizing the trade-offs between performance and energy efficiency. Advanced methodologies, including dynamic data placement strategies, locality-aware scheduling, and innovative reduce task placement techniques, are reviewed in depth. Additionally, we highlight the importance of network power effectiveness (NPE) and examine the role of optical and electronic switching technologies in enhancing data center efficiency. By synthesizing findings from recent studies, this paper provides valuable insights into the optimization of cloud data centers, offering recommendations for improving resource utilization and reducing job completion times while maintaining energy efficiency. The findings contribute to the ongoing efforts to scale and adapt cloud data infrastructures for the rapidly growing demands of big data applications.
Keywords:
Cloud Data Centers; Big Data Optimization; Hadoop Clusters; Job Scheduling Algorithms; Network Topology Efficiency
Full text article in PDF:
Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
