Energy wasting at internet data centers due to fear

Fernández-Montes, Alejandro; Fernández-Cerero, Damián; Abril, Luis González; Álvarez-García, Juan Antonio; Ramírez, Juan Antonio Ortega

doi:10.1016/j.patrec.2015.06.018

Cited by 18 publications

(10 citation statements)

References 27 publications

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“…Therefore, these facilities are usually under higher pressure during day-time hours than in night-time hours. This and other reasons, such as the fear of any change that could break operational requirements [5] , and the complexity of the systems involved, lead to an over-provision of data-center infrastructures. This decision leads to servers being kept underused or in an idle state, which is highly inefficient from an energy-consumption perspective.…”

Section: Introductionmentioning

confidence: 99%

SCORE: Simulator for cloud optimization of resources and energy consumption

Fernández-Cerero

Fernández-Montes

Jakóbik

et al. 2018

Simulation Modelling Practice and Theory

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Achieving efficiency both in terms of resource utilisation and energy consumption is a complex challenge, especially in large-scale wide-purpose data centers that serve cloudcomputing services. Simulation presents an appropriate solution for the development and testing of strategies that aim to improve efficiency problems before their applications in production environments. Various cloud simulators have been proposed to cover different aspects of the operation environment of cloud-computing systems. In this paper, we define the SCORE tool, which is dedicated to the simulation of energy-efficient monolithic and parallel-scheduling models and for the execution of heterogeneous, realistic and synthetic workloads. The simulator has been evaluated through empirical tests. The results of the experiments confirm that SCORE is a performant and reliable tool for testing energyefficiency, security, and scheduling strategies in cloud-computing environments.

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Section: Introductionmentioning

confidence: 99%

SCORE: Simulator for cloud optimization of resources and energy consumption

Fernández-Cerero

Fernández-Montes

Jakóbik

et al. 2018

Simulation Modelling Practice and Theory

Self Cite

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“…According to surveys on large-scale data centers within NH area, the parameters are outlined in Table 7. The average power consumption of a common server per CPU in on/off state is assumed as 200 W and 100 W based on [65]. According to the research, the ratio of on-site thermal power to on-site wind power is 4:4.5 [66] After adjusting some of the data, the results of this simulation model is shown as follows.…”

Section: ) Impact Estimation On North Hebeimentioning

confidence: 99%

Flexible Multi-Energy Scheduling Scheme for Data Center to Facilitate Wind Power Integration

2020

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Due to the intermittent and uncontrollable nature of wind resources and inflexible operation of conventional generation units, they present challenges for the power system to integrate more wind power. With its unique flexibility on the demand side, the data center can be considered as an effective solution to relieve wind curtailment. Moreover, with the help of waste heat recovery module, the data center can reduce the utilization of conventional thermal units especially in the residential heating sector which increases the flexibility of system operation and facilitates more renewable integration. In this paper, a flexible workload management and resource scheduling model are proposed to achieve a multi-energy co-optimization for data center and enhance the integration of wind power. A two-stage stochastic programming model is formulated to address the uncertainties involved in this process. The proposed model is examined by a simulative data center microgrid and the numerical results demonstrate its effectiveness and robustness. INDEX TERMS Data center, workload allocation, wind energy, waste heat recovery, energy management.

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“…One of the most popular approaches to increase efficiency is to switch off idle servers [75,78], which is usually tested in dedicated simulation tools [74]. Several models, including games theory models [72,73], are used to balance opposite requirements in data centers, such as performance and energy consumption.…”

Section: Software Solutions For Infrastructure Efficiencymentioning

confidence: 99%

Towards Efficient and Scalable Data-Intensive Content Delivery: State-of-the-Art, Issues and Challenges

Kilanioti

Fernández-Montes

Fernández-Cerero

et al. 2019

Lecture Notes in Computer Science

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This chapter presents the authors' work for the Case Study entitled "Delivering Social Media with Scalability" within the framework of High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) COST Action 1406. We identify some core research areas and give an outline of the publications we came up within the framework of the aforementioned action. The ease of user content generation within social media platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges: derivation of real-time meaningful insights from effectively gathered social information, a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general, etc. In this article we present the methodology we followed, the results of our work and the outline of a comprehensive survey, that depicts the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centers supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. The challenges of enabling better provisioning of social media data have been identified and they were based on the context of users accessing these resources. The existing literature has been systematized and the main research points and industrial efforts in the area were identified and analyzed. In our works, in the framework of the Action, we came up with

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Energy wasting at internet data centers due to fear

Cited by 18 publications

References 27 publications

SCORE: Simulator for cloud optimization of resources and energy consumption

SCORE: Simulator for cloud optimization of resources and energy consumption

Flexible Multi-Energy Scheduling Scheme for Data Center to Facilitate Wind Power Integration

Towards Efficient and Scalable Data-Intensive Content Delivery: State-of-the-Art, Issues and Challenges

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