PLDAD—An Algorihm to Reduce Data Center Energy Consumption

Abstract

Due to the demands of new technologies such as social networks, e-commerce and cloud computing, more energy is being consumed in order to store all the produced data. While these new technologies require high levels of availability, a reduction in the cost and environmental impact is also expected. The present paper proposes a power balancing algorithm (power load distribution algorithm-depth (PLDA-D)) to optimize the energy distribution of data center electrical infrastructures. The PLDA-D is based on the Bellman and Ford–Fulkerson flow algorithms that analyze energy-flow models (EFM). EFM computes the power efficiency, sustainability and cost metrics of data center infrastructures. To demonstrate the applicability of the proposed strategy, we present a case study that analyzes four power infrastructures. The results obtained show about a 3.8% reduction in sustainability impact and operational costs.

Cluster-Based Prediction for Batteries in Data Centers

“…Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, data centers are now major consumers of electrical energy [3]. In 2013, data centers in U.S.A. consumed 91 billion kilowatt-hours of electricity, and this was expected to continue to rise over the years [4]. In 2017, nearly 8 million data centers required an astronomical 416.2 terawatt-hours of electricity [5,6].…”

Clustered Based Prediction for Batteries in the Data Centers

“…Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, data centers are now major consumers of electrical energy [3]. In 2013, data centers in the U.S. consumed 91 billion kilowatt-hours of electricity, and this is expected to continue to rise [4]. In 2017, nearly 8 million data centers required an astronomical 416.2 terawatt-hours of electricity [5,6].…”