Principles of Green Data Mining

Schneider, Johannes; Basalla, Marcus; Seidel, Stefan

doi:10.24251/hicss.2019.250

Cited by 7 publications

(4 citation statements)

References 49 publications

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“…Furthermore, one might include more objectives, e.g. generating proposals that require little energy to process by the AI [14] or taking into account behavioral norms expected by people as common for social robots [3,17]. We hope that in the future human-to-AI coaches will help non-experts to better interact with AI systems.…”

Section: Discussionmentioning

confidence: 99%

Human-to-AI Coach: Improving Human Inputs to AI Systems

Schneider

2020

Lecture Notes in Computer Science

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Humans increasingly interact with Artificial intelligence (AI) systems. AI systems are optimized for objectives such as minimum computation or minimum error rate in recognizing and interpreting inputs from humans. In contrast, inputs created by humans are often treated as a given. We investigate how inputs of humans can be altered to reduce misinterpretation by the AI system and to improve efficiency of input generation for the human while altered inputs should remain as similar as possible to the original inputs. These objectives result in trade-offs that are analyzed for a deep learning system classifying handwritten digits. To create examples that serve as demonstrations for humans to improve, we develop a model based on a conditional convolutional autoencoder (CCAE). Our quantitative and qualitative evaluation shows that in many occasions the generated proposals lead to lower error rates, require less effort to create and differ only modestly from the original samples.

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Section: Discussionmentioning

confidence: 99%

Human-to-AI Coach: Improving Human Inputs to AI Systems

Schneider

2020

Lecture Notes in Computer Science

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“…All the introduced approaches attempt to enable energy awareness in cloud applications, but the workflow enhancement perspective is missing. Some solutions have been proposed for specific types of applications as by Schneider, Basalla, and Seidel, where guidelines are provided for designing Data Mining tasks [40]. Aligning with current trends in cloud application design, we decide to focus on cloud-native applications.…”

Section: State Of the Artmentioning

confidence: 99%

Enriching Cloud-native Applications with Sustainability Features

Vitali,

Schmiedmayer,

Bootz

2023

2023 IEEE International Conference on Cloud Engineering (IC2E)

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Due to the ever-growing demand for computational resources, the environmental impact of data centers is continuously increasing. Recently, a great effort has been made to mitigate this impact, while the demand for computational resources has continued to grow. Current mitigation strategies focus on the infrastructure perspective, while the application perspective has been neglected. This paper aims to engage application designers and developers on the path to greener application design. Following the Sustainable Application Design Process (SADP) methodology, we introduce a Sustainable Application Design Architecture (SADA) for enriching cloud-native application components with sustainability features that can be exploited to adapt the application workflow to the environmental context. The architecture enables synergies from design to deployment between all stakeholders involved in the application management. The paper focuses on enriching the application with sustainability features in the design and development phases. We also present and discuss a prototype that can translate designlevel sustainability features into development features.

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“…Some proposal aimed to estimate energy efficiency of specific applications in embedded systems [11], but cannot be applied in complex cloud infrastructures. From a design perspective, in [30] more specific guidelines are provided focusing only on data mining. Current research mainly focuses on dynamic resource allocation and scheduling according to energy efficiency optimization [4] [35].…”

Section: State Of the Artmentioning

confidence: 99%

“…Thus, the problem is how to motivate application providers to invest in sustainable applications. Existing studies have demonstrated how sustainability can become a strategic value for both organizations and their customers thanks to a proper awareness of the impact on the environment [30].…”

Section: Feasibility and Open Challengesmentioning

confidence: 99%

Towards Greener Applications: Enabling Sustainable-aware Cloud Native Applications Design

Vitali

2022

Advanced Information Systems Engineering

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Data centers energy demand is increasing. While a great deal of effort has been made to reduce the amount of CO2 generated by large cloud providers, too little has been done from the application perspective. We claim that application developers can impact the environmental footprint by enhancing the application design with additional features. Following the proposed Sustainable Application Design Process (SADP), the application design is enriched with information that can be leveraged by cloud providers to manage application execution in an energyaware manner. This exploratory work aims to emphasize the awareness on the sustainability of applications by proposing a methodology for its evaluation. To this end, we first suggest possible actions to enrich the application design towards sustainability, and finally describe how this additional information can be leveraged in the application workflow. We discuss the feasibility of our methodology by referring to existing tools and technologies capable of supporting the design features proposed in a production environment.

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Principles of Green Data Mining

Cited by 7 publications

References 49 publications

Human-to-AI Coach: Improving Human Inputs to AI Systems

Human-to-AI Coach: Improving Human Inputs to AI Systems

Enriching Cloud-native Applications with Sustainability Features

Towards Greener Applications: Enabling Sustainable-aware Cloud Native Applications Design

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