Implementation of a Server Cluster in the Cloud to Optimize Information Management

Implementation of a Server Cluster in the Cloud to Optimize Information Management

© 2023 by IJETT Journal
Volume-71 Issue-2
Year of Publication : 2023
Author : Mauro Canales Zapata, Laberiano Andrade-Arenas
DOI : 10.14445/22315381/IJETT-V71I2P226

How to Cite?

Mauro Canales Zapata, Laberiano Andrade-Arenas, "Implementation of a Server Cluster in the Cloud to Optimize Information Management," International Journal of Engineering Trends and Technology, vol. 71, no. 2, pp. 228-235, 2023. Crossref,

In this work, the implementation of a cluster of servers in the cloud is carried out to optimize the information management of the company Obuma SPA; this solution aims to optimize the performance of computer applications, provide the scalability of data servers through various elements that make up the proposed topology. The development of this solution will be carried out with the MariaDB database engine, and within the Linux operating system, specifically with the Centos distribution in version 7, which is specifically oriented towards a corporate segment. It is important to know that this implementation greatly benefits the organization because it allows it to offer its services to many more clients since, currently, the company does not invest in advertising for fear that the servers will collapse. For this reason, the need to improve the performance of all its web applications and maintain satisfaction for each of its customers.

Applications, Cluster, Computer Science, Performance, Scalability.

[1] A. Mahgoubet al., Optimuscloud: Heterogeneous Configuration Optimization for Distributed Databases in the Cloud, Usenix Association, 2020. [Online]. Available:
[2] Alberto Ceselli, Marco Premoli, and Stefano Secci, “Mobile Edge Cloud Network Design Optimization,” IEEE/ACM Transactions on Networking, vol. 25, no. 3, pp. 1818–1831, 2017 Crossref,
[3] Mohamed. I.El-Shenawy, Hayam Mousa, and Khaled M. Amin, “Enhancing Web Application Using Adaptive Containerized Application Placement Based on Clustering and Content Caching in The Cloud Environment,” International Journal of Engineering Trends and Technology, vol. 70, no. 1, pp. 164–170, 2022. Crossref,
[4] Zhiping Peng et al., “A Multi-Objective Trade-Off Framework for Cloud Resource Scheduling Based on the Deep Q-Network Algorithm,” Cluster Computing, vol. 23, no. 4, pp. 2753–2767, 2020. Crossref,
[5] M Chaitanya Kumari, and P Nagendra Babu, “Survey on Clustering on the Cloud by Using Map Reduce in Large Data Applications,” International Journal of Engineering Trends and Technology, vol. 21, no. 8, pp. 392–395, 2015. Crossref,
[6] Zhou Zhou et al., “Virtual Machine Migration Algorithm for Energy Efficiency Optimization in Cloud Computing,” Concurrency and Computation: Practice and Experience, vol. 30, no. 24, p. e4942, 2018. Crossref,
[7] Mandeep Singh, and Shashi Bhushan, “CS Optimized Task Scheduling for Cloud Data Management,” International Journal of Engineering Trends and Technology, vol. 70, no. 6, pp. 114–121, Jun. 2022, Crossref,
[8] T. P. Shabeera et al., “Optimizing VM Allocation and Data Placement for Data-Intensive Applications in Cloud Using ACO Metaheuristic Algorithm,” Engineering Science and Technology, An International Journal, vol. 20, no. 2, pp. 616–628, 2017. Crossref,
[9] Itsuro Kita et al., “Emission of Magmatic He with Different 3He/4He Ratios from the Unzen Volcanic Area, Japan,” Geochemical Journal, vol. 27, no. 4–5, pp. 251–259, 1993. Crossref,
[10] Lejiang Guo et al., “The Building of Cloud Computing Environment for E-Health,” 2010 International Conference on E-Health Networking, Digital Ecosystems and Technologies, EDT 2010, vol. 1, pp. 89–92, 2010. Crossref,
[11] B. Murugeshwari et al., "Effective Data Aggregation in WSN for Enhanced Security and Data Privacy," SSRG International Journal of Electrical and Electronics Engineering, vol. 9, no. 11, pp. 1-10, 2022. Crossref,
[12] Maciej Serda et al., “Syntezaiaktywnośćbiologicznanowychanalogówtiosemikarbazonowychchelatorówżelaza,” Uniwersytetśląski, vol. 7, no. 1, pp. 343–354, 2013. Crossref,
[13] Yeliz Karaca, “Mobile Cloud Computing Based Stroke Healthcare System,” International Journal of Information Management, vol. 45, pp. 250–261, 2019. Crossref,
[14] Jun Wu et al., “Big Data Analysis-Based Secure Cluster Management for Optimized Control Plane in Software-Defined Networks,” IEEE Transactions on Network and Service Management, vol. 15, no. 1, pp. 27–38, 2018. Crossref,
[15] M. H. Ghahramani, Meng Chu Zhou, and Chi Tin Hon, “Toward Cloud Computing QoS Architecture: Analysis of Cloud Systems and Cloud Services,” IEEE/CAA Journal of Automatica Sinica, vol. 4, no. 1, pp. 6–18, 2017. Crossref,
[16] Muhammad Zakarya, and Lee Gilla, “Energy Efficient Computing, Clusters, Grids and Clouds: A Taxonomy and Survey,” Sustainable Computing: Informatics and Systems, vol. 14, pp. 13–33, 2017. Crossref,
[17] Yu Gan, and Christina Delimitrou, “The Architectural Implications of Cloud Microservices,” IEEE Computer Architecture Letters, vol. 17, no. 2, pp. 155–158, 2018. Crossref,
[18] Amir Javadpour et al., “Power Curtailment in Cloud Environment Utilising Load Balancing Machine Allocation,” IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation, pp. 1364-1370, 2018. Crossref,
[19] Dinh-Mao Bui et al., “Energy Efficiency for Cloud Computing System based on Predictive Optimization,” Journal of Parallel and Distributed Computing, vol. 102, pp. 103–114, 2017. Crossref,
[20] Manjunatha S, and Dr. Suresh L, "A Study on Consolidation of Data Servers in Virtualized Cloud Atmosphere," SSRG International Journal of Computer Science and Engineering, vol. 6, no. 11, pp. 47-50, 2019. Crossref,
[21] Apoorva Srivastava, Sukriti Bhardwaj, and Shipra Saraswat, “SCRUM Model for Agile Methodology,” Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2017, pp. 864–869, 2017. Crossref,
[22] Anabel Pilicita Garrido, Yolanda Borja Lopez, and Gonzalo Gutierrez Constant, “MariaDB and PostgreSQL Performance,” Scientific and Technological Magazine UPSE, vol. 7, no. 2, pp. 9–16, 2021. Crossref,
[23] Bagus Aditya, and Tutun Juhana, “A High Availability (HA) Mariadb Galera Cluster Across Data Center with Optimized WRR Scheduling Algorithm of LVS - TUN,” Proceeding of the 2015 9th International Conference on Telecommunication Systems Services and Applications, TSSA 2015, pp. 1-5, 2016, Crossref,
[24] Sampurna Dadi Riskiono, and Donaya Pasha, “Comparative Analysis of Server Load Balancing with Haproxy & Nginx in Supporting E-Learning Server Performance” InComTech: Journal of Telecommunications and Computers, vol. 10, no. 3, p. 135, 2020. Crossref,
[25] Jing-Wei Liu et al., “The Role of Sprint Planning and Feedback in Game Development Projects: Implications for Game Quality,” Journal of Systems and Software, vol. 154, pp. 79–91, 2019. Crossref,
[26] Luis Gonçalves, “Scrum,” Controlling & Management Review, vol. 62, no. 4, pp. 40–42, 2018. Crossref, 018-0020-3
[27] Korada Kishore Kumar, and Konni Srinivasa Rao, “An Efficient users Authentication and Secure Data Transmission of Cluster based Wireless Sensor Network," SSRG International Journal of Computer Science and Engineering, vol. 5, no. 1, pp. 1-5, 2018. Crossref,
[28] Qiang Li, “The Use of Artificial Intelligence Combined with Cloud Computing in the Design of Education Information Management Platform,” International Journal of Emerging Technologies in Learning (iJETL), vol. 16, no. 5, pp. 32–44, 2021. Crossref,
[29] Ken Schwaber, “SCRUM Development Process,” Business Object Design and Implementation, pp. 117–134, 1997. Crossref,