Energy-Efficient Networking Solutions in Cloud-Based Environments

Moghaddam, Fahimeh Alizadeh; Lago, Patricia; Grosso, Paola

doi:10.1145/2764464

Cited by 27 publications

(13 citation statements)

References 56 publications

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“…In the research literature, there are extensive surveys from slightly different points of view that cover approaches related to green networking [4,27,37,128,129].…”

Section: A Existing Classification Of Green Networking Approachesmentioning

confidence: 99%

“…Finally, sleeping/standby is founded on power management basics that allow network equipment (or parts of them) to be switched off, to enter very low power states. A recent survey [128] mainly focuses on energy efficient solutions for cloud-based networking components, making use of the system literature review (SLR) research method [129]. Four groups of methodologies have been identified based on the networking component granularity: (i) Data Center (DC) layer, (ii) Application (App) layer, (iii) Network layer, and (iv) Device layer.…”

Section: A Existing Classification Of Green Networking Approachesmentioning

confidence: 99%

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Energy saving in carrier-grade networks: A survey

Mâaloul

Fourati

Cousin

2018

Computer Standards & Interfaces

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Summary-Energy consumption of large-scale networks has become a primary concern in a society increasingly dependent on information technology. Novel solutions that contribute to achieving energy savings in wired networks have been proposed to mitigate ongoing and alarming climate change and global warming. A detailed survey of relevant power-saving approaches in wired networks is presented here. We give a special focus on carrier-grade networks. At first we perform a comprehensive study of communication infrastructures regarding energy saving. Then, we highlight key issues to enable green networks, ranging from network design to network operation. After that, we present the major contributors to power consumption in wireline networks. Afterwards, we survey, classify, and compare the main energyaware methods and mechanisms that are the most appropriate for improving the energy efficiency of carrier-grade networks.

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“…In the research literature, there are extensive surveys from slightly different points of view that cover approaches related to green networking [4,27,37,128,129].…”

Section: A Existing Classification Of Green Networking Approachesmentioning

confidence: 99%

Section: A Existing Classification Of Green Networking Approachesmentioning

confidence: 99%

Energy saving in carrier-grade networks: A survey

Mâaloul

Fourati

Cousin

2018

Computer Standards & Interfaces

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“…Measuring VMs and containers is quite difficult as resources are not equally shared [43]. Many clouds use oversubscription, whereby resources are over promised to many services with the hope that these services do not need all of these resources at the same time.…”

Section: Virtualizationmentioning

confidence: 99%

“…Currently there is some work on attributing energy consumption to virtualized machines [44], [43], but it is just the beginning of such research. Little to no work has been done to estimate the energy use of services within containers such as docker.…”

Section: Virtualizationmentioning

confidence: 99%

Green software engineering: the curse of methodology

Hindle

2015

Preprint

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Computer Science often seems distant from its natural science cousins, especially software engineering which feels closer to sociology and psychology than to physics. Physical measurements are often rare in software engineering, except in a few niches. One such important niche is that of software energy consumption, green mining, green IT, and sustainable computing, which all fall under the umbrella of green software engineering.With the physical measurement of energy consumption comes all of the limitations of measurement and experimentation that exist in the natural sciences and engineering.Issues abound, from attribution of energy use, isolation of components, to replicable experiments. These get further complicated by cloud computing whereby systems are virtualized and attribution of resource usage is a serious issue. Thus in this work we discuss the current state of software energy consumption, and where will it go. Abstract-Computer Science often seems distant from its natural science cousins, especially software engineering which feels closer to sociology and psychology than to physics. Physical measurements are often rare in software engineering, except in a few niches. One such important niche is that of software energy consumption, green mining, green IT, and sustainable computing, which all fall under the umbrella of green software engineering.With the physical measurement of energy consumption comes all of the limitations of measurement and experimentation that exist in the natural sciences and engineering. Issues abound, from attribution of energy use, isolation of components, to replicable experiments. These get further complicated by cloud computing whereby systems are virtualized and attribution of resource usage is a serious issue.Thus in this work we discuss the current state of software energy consumption, and where will it go.

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“…Given SDNs wide range of applications and their rapid growth in data center networks, they are often chosen as part of the power efficient solutions. In an earlier systematic literature review [3], we studied the existing energy efficient networking solutions and we observed a growing trend in using SDNs combined with energy awareness. The existing energy efficient networking solutions are implemented as flow schedulers that fullfill user-defined quality requirements while considering energy consumption improvements.…”

Section: Introductionmentioning

confidence: 99%

Linear programming approaches for power savings in software-defined networks

Moghaddam¹,

Grosso

2016

2016 IEEE NetSoft Conference and Workshops (NetSoft)

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Abstract-Software-defined networks have been proposed as a viable solution to decrease the power consumption of the networking component in data center networks. Still the question remains on which scheduling algorithms are most suited to achieve this goal. We propose 4 different linear programming approaches that schedule requested traffic flows on SDN switches according to different objectives. Depending on pre-defined software quality requirements such as delay and performance, a single variation or a combination of variations can be selected to optimize the power saving and the performance metrics. Our simulation results demonstrate that all our algorithm variations outperform the shortest path scheduling algorithm, our baseline on power savings, less or more strongly depending on the power model chosen. We show that in FatTree networks, where switches can save up to 60% of power in sleeping mode, we can achieve 15% minimum improvement assuming a one-to-one traffic scenario. Two of our algorithm variations privilege performance over power saving and still provide around 45% of the maximum achievable savings.

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Energy-Efficient Networking Solutions in Cloud-Based Environments

Cited by 27 publications

References 56 publications

Energy saving in carrier-grade networks: A survey

Energy saving in carrier-grade networks: A survey

Green software engineering: the curse of methodology

Linear programming approaches for power savings in software-defined networks

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