Increasing Energy Efficiency in Data Centers Using Energy Management

Dumitru, Iulia; Făgărăşan, Ioana; Iliescu, Sergiu Stelian; Said, Yanis Hadj; Ploix, Stéphane

doi:10.1109/greencom.2011.53

Cited by 8 publications

(9 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dumitru et al 30 presented a technique to increase energy management in data centers but did not give implementation details of the proposed solution. Pedram 31 proposed a solution for energy-efficient data centers based on performance measurement metrics, but the solution was not practical application in large tier-level CDCs.…”

Section: Related Workmentioning

confidence: 99%

Server consolidation: A technique to enhance cloud data center power efficiency and overall cost of ownership

Uddin

Hamdi

Alghamdi

et al. 2021

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Cloud computing is a well-known technology that provides flexible, efficient, and cost-effective information technology solutions for multinationals to offer improved and enhanced quality of business services to end-users. The cloud computing paradigm is instigated from grid and parallel computing models as it uses virtualization, server consolidation, utility computing, and other computing technologies and models for providing better information technology solutions for large-scale computational data centers. The recent intensifying computational demands from multinationals enterprises have motivated the magnification for large complicated cloud data centers to handle business, monetary, Internet, and commercial applications of different enterprises. A cloud data center encompasses thousands of millions of physical server machines arranged in racks along with network, storage, and other equipment that entails an extensive amount of power to process different processes and amenities required by business firms to run their business applications. This data center infrastructure leads to different challenges like enormous power consumption, underutilization of installed equipment especially physical server machines, CO2 emission causing global warming, and so on. In this article, we highlight the data center issues in the context of Pakistan where the data center industry is facing huge power deficits and shortcomings to fulfill the power demands to provide data and operational services to business enterprises. The research investigates these challenges and provides solutions to reduce the number of installed physical server machines and their related device equipment. In this article, we proposed server consolidation technique to increase the utilization of already existing server machines and their workloads by migrating them to virtual server machines to implement green energy-efficient cloud data centers. To achieve this objective, we also introduced a novel Virtualized Task Scheduling Algorithm to manage and properly distribute the physical server machine workloads onto virtual server machines. The results are generated from a case study performed in Pakistan where the proposed server consolidation technique and virtualized task scheduling algorithm are applied on a tier-level data center. The results obtained from the case study demonstrate that there are annual power savings of 23,600 W and overall cost savings of US$78,362. The results also highlight that the utilization ratio of already existing physical server machines has increased to 30% compared to 10%, whereas the number of server machines has reduced to 50% contributing enormously toward huge power savings.

show abstract

Section: Related Workmentioning

confidence: 99%

Server consolidation: A technique to enhance cloud data center power efficiency and overall cost of ownership

Uddin

Hamdi

Alghamdi

et al. 2021

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…Virtualization facilitates consolidation by supporting multiple independent virtual machines on one physical server (Shuja et al , 2012). These two techniques are widely used to increase utilization levels and improve DC EE (Dumitru et al , 2011). Using DVFS techniques also improves EE by decreasing the operating power of servers, but it also affects performance (Kaxiras and Martonosi, 2008).…”

Section: Related Workmentioning

confidence: 99%

EEUI: a new measure to monitor and manage energy efficiency in data centers

Abaunza

Hameri

Niemi

2018

IJPPM

View full text Add to dashboard Cite

Purpose Data centers (DCs) are similar to traditional factories in many aspects like response time constraints, limited capacity, and utilization levels. Several indicators have been developed to monitor and compare productivity in manufacturing. However, in DCs most used indicators focus on technical aspects of infrastructure, not efficiency of operations. The purpose of this paper is to rely on operations management to define a commensurate and proportionate DC performance indicator: the energy-efficient utilization indicator (EEUI). EEUI makes objective and comparative assessment of efficiency possible independently of the operating environment and its constraints. Design/methodology/approach The authors followed a design science approach, which follows the practitioner’s initial steps for finding solutions to business relevant problems prior to theory building. Therefore, this approach fits well with this research, as it is primarily motivated by business and management needs. EEUI combines both the amount of energy consumed by different components and their current energy efficiency (EE). It reaches its highest value when all server components are optimally loaded in EE sense. The authors tested EEUI by collecting data from three scientific DCs and performing controlled laboratory tests. Findings The results indicate that the optimization of EEUI makes it possible to run computing resources more efficiently. This leads to a higher EE and throughput of the DC while reducing the carbon footprint associated to DC operations. Both energy-related costs and the total cost of ownership are consequently reduced, since the amount of both energy and hardware resources needed decrease, while improving DC sustainability. Practical implications In comparison with current DC operations, the results imply that using the EEUI could help increase the EE of DCs. In order to optimize the proposed EEUIs, DC managers and operators should use resource management policies that increase the resource usage variation of the jobs being processed in the same computing resources (e.g. servers). Originality/value The paper provides a novel approach to monitor the EE at which computing resources are used. The proposed indicator not only considers the utilization levels at which server components are used but also takes into account their EE and energy proportionality.

show abstract

“…2(b). In a second step, all loops are aggregated and finally replaced by one task resulting in the further 26 P.J. Kuehn reduced task graph shown in Fig.…”

Section: Example Of a Task Graph Reductionmentioning

confidence: 99%

“…UPS, switch gear, generators, PDUs, batteries, networking and connecting equipment). The total power consumed by a typical data center is broken down into previous categories as follow [22,26,27]: IT equipment (30 ÷ 60 %); cooling plant: (25 ÷ 40 %); power conditioning system (8 ÷ 15 %); lighting/security (1 ÷ 3 %); delivery components and others (5 ÷ 15 %).…”

Section: Power and Energy Consumption Metricsmentioning

confidence: 99%