Automation in Telecom Data Centers: Enhancing Efficiency and Uptime

Ernest Suzuki

Abstract


The growing demand for high-speed connectivity, cloud services, and 5G networks has placed immense pressure on telecom data centers to operate at maximum efficiency while ensuring near-zero downtime. Automation technologies, including AI-driven resource management, robotic process automation (RPA), and predictive maintenance systems, are transforming how telecom data centers are managed. This paper examines the role of automation in enhancing data center efficiency, reducing energy consumption, and improving uptime. Case studies highlight how automated systems reduce human error, enhance operational resilience, and optimize resource utilization.

Keywords


data centers, automation, AI, predictive maintenance.

References


Purmonen, Arttu. Intelligent Tools to Increase Uptime in The HFC Plant. Teleste Corporation, 2017.

Anderson, Sean F. “Improving Data Center Efficiency”. Energy Engineering, vol. 107, no. 5, Taylor & Francis, 2010, pp. 42–63.

Harison, Elad, and Ofer Barkai. “Automating the Improvement of Service Quality: The TELCO Case”. Journal of Business Case Studies (Online), vol. 7, no. 6, The Clute Institute, 2011, p. 81.

Matko, Vojko, and Barbara Brezovec. “Improved Data Center Energy Efficiency and Availability with Multilayer Node Event Processing”. Energies, vol. 11, no. 9, MDPI, 2018, p. 2478.

Mehta, Gitanjali, et al. “Application of IoT to Optimize Data Center Operations”. 2018 International Conference on Computing, Power and Communication Technologies (GUCON), IEEE, 2018, pp. 738–742.

Levy, Moises, and Jason O. Hallstrom. “A New Approach to Data Center Infrastructure Monitoring and Management (DCIMM)”. 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), IEEE, 2017, pp. 1–6.

Geng, Hwaiyu. Data Center Handbook. John Wiley & Sons, 2014.

Levy, Moises, and Daniel Raviv. “A Novel Framework for Data Center Metrics Using a Multidimensional Approach”. 15th LACCEI International Multi-Conference for Engineering, Education, and Technology: Global Partnerships for Development and Engineering Education, 2017.

Mares, K. C. Demand Response and Open Automated Demand Response Opportunities for Data Centers. 2009.

Faccioni Filho, Mauro, and Moacyr Franco Neto. Data Center Infrastructure Management and Automation Systems: An Evaluation Method. CAINE--2012, 25th International Conference on Computer Applications in Industry and Engineering, New Orleans, USA, 2012.


Refbacks

  • There are currently no refbacks.


Bookmark and Share


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.