Cloud Computing and Energy Efficiency: Mapping the Thematic Structure of Research

Lis, Andrzej; Sudolska, Agata; Pietryka, Ilona; Kozakiewicz, Adam

doi:10.3390/en13164117

Cited by 20 publications

(18 citation statements)

References 58 publications

(121 reference statements)

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“…Total ICT power Power consumed by network equipment , (1) which is the equivalent to the portion of network equipment on the PUE, and the Communication Network Energy Efficiency (CNEE), which may be defined as "energy to deliver a single bit of information" [5]:…”

Section: Npue =mentioning

confidence: 99%

“…Data center networks are increasing in size, data processing capacity and throughput to attend to the high demand of computing services required by: the growing demand on the cloud [1], smart cities, the advent of the Internet of Things (IoT), big data applications and deep neural networks among other technologies. The demand from DC for energy and its related environmental implications are increasing accordingly.…”

Section: Introductionmentioning

confidence: 99%

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Improving Energy Efficiency on SDN Control-Plane Using Multi-Core Controllers

2021

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Software-defined networks have become more common in data centers. The programmability of these networks is a great feature that allows innovation to be deployed fast, following the increasing number of new applications. This growth comes with a cost of more processing power and energy consumption. Many researchers have tackled this issue using existing routing techniques to dynamically adjust the network forwarding plane to save energy. On the control-plane, researchers have found algorithms for positioning the controller in a way to reduce the number of used links, thus reducing energy. These strategies reduce energy consumption at the expense of processing power of the controllers. This paper proposes a novel approach to energy efficiency focused on the network’s control-plane, which is complementary to the many already existing data-plane solutions. It takes advantage of the parallel processing capabilities of modern off-the-shelf multicore processors to split the many tasks of the controller among the cores. By dividing the tasks among homogeneous cores, one can lower the frequency of operations, lowering the overall energy consumption while keeping the same quality of service level. We show that a multicore controller can use an off-the-shelf multicore processor to save energy while keeping the level of service. We performed experiments based on standard network measures, namely latency and throughput, and standard energy efficiency metrics for data centers such as the Communication Network Energy Efficiency (CNEE) metric. Higher energy efficiency is achieved by a parallel implementation of the controller and lowering each core’s frequency of operation. In our experiments, we achieved a drop of 28% on processor energy use for a constant throughput scenario when comparing with the single-core approach.

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Section: Npue =mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving Energy Efficiency on SDN Control-Plane Using Multi-Core Controllers

2021

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“…According to A. Prichard [72], bibliometrics is a set of research techniques that can be used in analysing publications. Presently, bibliometric analysis is a widely used research method, allowing authors to systematically review literatures (e.g., [73]), map the thematic structures of selected terminology (e.g., [74]), and identify research trends (e.g., [68]).…”

Section: Bibliometric Analysismentioning

confidence: 99%

The Morphology and Differentiation of the Content of International Debate on Renewable Energy. A Bibliometric Analysis of Web of Science, Scopus, and Twitter

Sanak-Kosmowska

Wiktor

2021

Energies

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This paper aims to identify a bibliometric profile, presenting the results of research and debates in social media on renewable energy sources (RES). It analyses current scientific publications (2019–2021) and tweets posted in July 2021 by international Twitter users. The subject of the study is an analysis of key words in articles, the results of research, and the content of tweets (hashtags #renewables) related to renewable energy (RE) as well as an assessment of the morphology of content and the degree of its differentiation in the analysed data resources. The conducted analysis facilitates an assessment of similarities of key words in scientific papers and the content of debates in social media—on Twitter, a global platform. In its methodological dimension, the work is based on a bibliometric analysis (articles in both bases) and the analysis of Twitter data. This methodological approach allows for identifying the main trend, profile, and bibliometric characteristics of scientific papers representing two streams of information: articles in bases and the content (hashtags) of authentic and unguided international debates on Twitter. The focus on this platform results from a great popularity of social media as a platform for social debate, expressing comments and opinions and providing an opportunity to gain understanding of social, cultural, and environmental issues related to renewable energy sources from the perspective of social media participants. The objective of the paper and the proposed methodological approach relates to a knowledge gap in the area of renewable energy, and, more specifically, climate change and sustainable development.

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“…However, existing scheduling models induces high communication cost among processors because of high memory resource usage and routing overhead. Inter-processor communication cost is very high using existing techniques as well as these algorithms are relied upon a classic model which is not realistic when applied to a hybrid cloud environment (29)(30)(31) . In recent times workflow scheduling adopting cloud computational environments have been widely studied in (31) .…”

Section: Introductionmentioning

confidence: 99%

“…Inter-processor communication cost is very high using existing techniques as well as these algorithms are relied upon a classic model which is not realistic when applied to a hybrid cloud environment (29)(30)(31) . In recent times workflow scheduling adopting cloud computational environments have been widely studied in (31) . For overcoming research issues this paper presents a delay-aware and performance-efficient energy-optimized workflow execution model for a hybrid cloud environment.…”

Section: Introductionmentioning

confidence: 99%