Verizon’s Network Operations team are on the cutting edge of energy efficiency. Techerati spoke to machine learning project leader Oliver Prislan
Over the past few decades, technological advances have enabled telecom service providers to consolidate their network infrastructure. The reduction in equipment size, coupled with an improved ability to bridge larger distances, has also allowed service providers to reduce their data centre footprint.
But with the reduction in data centre sites, the modern facility has also become comparatively supersized and energy hungry, mainly due to the never-ending increase of network traffic. To mitigate this challenge, companies such as Verizon are turning to machine learning and data analytics to improve the energy efficiency of facilities.
Over the past four years, in Verizon’s Network Operations, a team led by Oliver Prislan have been applying the latest machine learning methods to forge sophisticated models that improve energy efficiency. Reams of complex data are fed to sensor networks (which transmit data to a centralised analytics platform), providing the information that helps the company reduce operational costs. The team is also simultaneously educating society about the impact of energy hungry data centres on the environment with speaking opportunities at seminars and shows, including Data Centre World Frankfurt next week.
Oliver acquired his master’s in electrical engineering (with a focus on process automation) at the University of Wuppertal — a pioneer in the field of neural networks. The ubiquitous machine learning tools used today – Python and TensorFlow – are based on the same principles Oliver studied in the 90s. He cultivated his knowledge in algorithmic research before entering his current career as manager of Verizon’s global network operations.
Combating cooling costs
When the European Union released its Energy Efficiency Directive policy, Verizon tasked Oliver with auditing the company’s data centre energy consumption.
The bulk of any data centre power consumption is based on the energy consumed by a centre’s cooling systems – in fact, cooling systems account for roughly 38 percent of the operating costs. It is estimated that the proper optimisation of a cooling system can slash operating costs by 25 percent.
Armed with the latest sensors, Oliver began to measure how Verizon’s cooling systems interacted with its data centre fleet, taking stock of variables such as ambient temperature, water temperature and the heat generated by IT systems.