GreenDCN: A General Framework for Achieving Energy Efficiency in Data Center Networks

Wang, Lin; Zhang, Fa; Aroca, Jordi Arjona; Vasilakos, Athanasios V.; Zheng, Kai; Hou, Chenying; Li, Dan; Li, Yong

doi:10.1109/jsac.2014.140102

Cited by 145 publications

(55 citation statements)

References 38 publications

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“…Unlike most similar works where the objective is to minimize cost or to maximize performance, the authors minimize the total power consumption of the network. Other works that consider switching off network components and sleep mode for saving energy can be found in [36][37][38][39][40][41][42][43].…”

Section: Related Workmentioning

confidence: 99%

Green Approach for Joint Management of Geo-Distributed Data Centers and Interconnection Networks

et al. 2017

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Every time an Internet user downloads a video, shares a picture, or sends an email, his/her device addresses a data center and often several of them. These complex systems feed the web and all Internet applications with their computing power and information storage, but they are very energy hungry. The energy consumed by Information and Communication Technology (ICT) infrastructures is currently more than 4% of the worldwide consumption and it is expected to double in the next few years. Data centers and communication networks are responsible for a large portion of the ICT energy consumption and this has stimulated in the last years a research effort to reduce or mitigate their environmental impact. Most of the approaches proposed tackle the problem by separately optimizing the power consumption of the servers in data centers and of the network. However, the Cloud computing infrastructure of most providers, which includes traditional telcos that are extending their offer, is rapidly evolving toward geographically distributed data centers strongly integrated with the network interconnecting them. Distributed data centers do not only bring services closer to users with better quality, but also provide opportunities to improve energy efficiency exploiting the variation of prices in different time zones, the locally generated green energy, and the storage systems that are becoming popular in energy networks. In this paper, we propose an energy aware joint management framework for geo-distributed data centers and their interconnection network. The model is based on virtual machine migration and formulated using mixed integer linear programming (MILP). It can be solved using state-of-the art solvers such as CPLEX in reasonable time. The proposed approach covers various aspects of Cloud computing systems. Alongside, it jointly manages the use of green and brown energies using energy storage technologies. The obtained results show that significant energy cost savings can be achieved compared to a baseline strategy, in which data centers do not collaborate to reduce energy and do not use the power coming from renewable resources.

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Section: Related Workmentioning

confidence: 99%

Green Approach for Joint Management of Geo-Distributed Data Centers and Interconnection Networks

et al. 2017

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“…On the other hand, it was not possible to find in literature a detailed consumption profile for the network switches. Thus, we considered the values provided in [22]. Table I summarizes the values used for the different profiles.…”

Section: B Power Consumption Modelsmentioning

confidence: 99%

Power comparison of cloud data center architectures

Ruiu

Bianco

Fiandrino

et al. 2016

2016 IEEE International Conference on Communications (ICC)

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Abstract-Power consumption is a primary concern for cloud computing data centers. Being the network one of the nonnegligible contributors to energy consumption in data centers, several architectures have been designed with the goal of improving network performance and energy-efficiency. In this paper, we provide a comparison study of data center architectures, covering both classical two-and three-tier design and state-of-art ones as Jupiter, recently disclosed by Google. Specifically, we analyze the combined effect on the overall system performance of different power consumption profiles for the IT equipment and of different resource allocation policies. Our experiments, performed in small and large scale scenarios, unveil the ability of network-aware allocation policies in loading the the data center in a energyproportional manner and the robustness of classical two-and three-tier design under network-oblivious allocation strategies.

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“…Wang et al [20] proposed a general framework for saving energy in modern data centers based on traffic engineering and virtualization techniques. It characterizes three different traffic patterns and, depending on the pattern, carries out advanced engineering traffic planning.…”

Section: Related Workmentioning

confidence: 99%

Smart Monitoring Embedded Service for Energy-Efficient and Sustainable Management in Data Centers

et al. 2016

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Information technologies (IT) currently represent 2% of CO 2 emissions. In recent years, a wide variety of IT solutions have been proposed, focused on increasing the energy efficiency of network data centers. Monitoring is one of the fundamental pillars of these systems, providing the information necessary for adequate decision making. However, today's monitoring systems (MSs) are partial, specific and highly coupled solutions. This study proposes a model for monitoring data centers that serves as a basis for energy saving systems, offered as a value-added service embedded in a device with low cost and power consumption. The proposal is general in nature, comprehensive, scalable and focused on heterogeneous environments, and it allows quick adaptation to the needs of changing and dynamic environments. Further, a prototype of the system has been implemented in several devices, which has allowed validation of the proposal in addition to identification of the minimum hardware profile required to support the model.

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GreenDCN: A General Framework for Achieving Energy Efficiency in Data Center Networks

Cited by 145 publications

References 38 publications

Green Approach for Joint Management of Geo-Distributed Data Centers and Interconnection Networks

Green Approach for Joint Management of Geo-Distributed Data Centers and Interconnection Networks

Power comparison of cloud data center architectures

Smart Monitoring Embedded Service for Energy-Efficient and Sustainable Management in Data Centers

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