A protocol for quantifying the carbon reductions achieved through the provision of low or zero carbon ICT services

Steenhof, Paul A.; Weber, Christopher L.; Brooks, Martin; Spence, John D.; Robinson, Randall; Simmonds, Rob; Kiddle, Cameron; Aikema, David; Savoie, Michel; Ho, Bobby; Lemay, Mathieu; Fung, J. W.; Cheriet, Mohamed

doi:10.1016/j.suscom.2012.01.001

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…However, as computing demand grows, so does the electricity consumption and the emission of greenhouse gas. Low carbon cloud computing has been proposed to limit the carbon emissions of cloud by many studies [1], [2]. For example, Canada's Greenstar Network [1] connects cloud computing resources directly to wind turbines or solar power generators, using green energy to reduce carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

Service Management and Energy Scheduling Toward Low-Carbon Edge Computing

Zhang

Wang

et al. 2023

IEEE Trans. Sustain. Comput.

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Edge computing has become an alternative low-latency provision of cloud computing thanks to its close-proximity to the users, and the geo-distribution nature of edge servers enables the utilization green energy from the environment on-site. To pursue the goal of low-carbon edge computing, it is desirable to minimize the operational expenditure by scheduling the computing resource and green energy according to the spatially and temporally varying user demands. In this paper, inspired by the successful application of deep reinforcement learning (DRL) in diverse domains, we propose a DRL-based edge computing management strategy which continuously explores the states and adaptively makes decisions on service management and energy scheduling, towards long-term cost minimization. Different from model-based solutions, our proposal is a model-free method, without any assumption on statistical knowledge as a priori, and therefore is practical in implementation. To speedup the agent training procedure, we further design a prioritized replay memory by utilizing the model-based solution as a guideline to set the transition priority. Extensive experiment results based on real-world traces validate that our proposed DRL-based strategy can make considerably progress compared to the one-shot greedy strategy, and it can learn the system dynamically to manage the edge computing services at runtime.

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Section: Introductionmentioning

confidence: 99%

Service Management and Energy Scheduling Toward Low-Carbon Edge Computing

Zhang

Wang

et al. 2023

IEEE Trans. Sustain. Comput.

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The cyber-consciousness of environmental assessment: how environmental assessments evaluate the impacts of smart, connected, and digital technology

Mulrow

Gali

Grubert

2021

Environ. Res. Lett.

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Digitally-enabled technologies are increasingly cyber-physical systems (CPS). They are networked in nature and made up of geographically dispersed components that manage and control data received from humans, equipment, and the environment. Researchers evaluating such technologies are thus challenged to include CPS subsystems and dynamics that might not be obvious components of a product system. Although analysts might assume CPS have negligible or purely beneficial impact on environmental outcomes, such assumptions require justification. As the physical environmental impacts of digital processes (e.g., cryptocurrency mining) gain attention, the need for explicit attention to CPS in environmental assessment becomes more salient. This review investigates how the peer-reviewed environmental assessment literature treats environmental implications of CPS, with a focus on journal articles published in English between 2010-2020. We identify nine CPS subsystems and dynamics addressed in this literature: energy system, digital equipment, non-digital equipment, automation & management, network infrastructure, direct costs, social & health effects, feedbacks, and cybersecurity. Based on these categories, we develop a “cyber-consciousness score” reflecting the extent to which the 115 studies that met our evaluation criteria address CPS, then summarize analytical methods and modeling techniques drawn from reviewed literature to facilitate routine inclusion of CPS in environmental assessment. We find that, given challenges in establishing system boundaries, limited standardization of how to evaluate CPS dynamics, and failure to recognize the role of CPS in a product system under evaluation, the extant environmental assessment literature in peer-reviewed journals largely ignores CPS subsystems and dynamics when evaluating digital or digitally-enabled technologies.

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A protocol for quantifying the carbon reductions achieved through the provision of low or zero carbon ICT services

Cited by 2 publications

References 6 publications

Service Management and Energy Scheduling Toward Low-Carbon Edge Computing

Service Management and Energy Scheduling Toward Low-Carbon Edge Computing

The cyber-consciousness of environmental assessment: how environmental assessments evaluate the impacts of smart, connected, and digital technology

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