Maze helps find ways to search more effiently, more accurately.

Asel Madiiarbekova

As cloud computing continues to expand rapidly, its environmental impact has become a pressing concern, particularly regarding energy consumption and resource utilization within data centers. This paper explores sustainable computing methods aimed at reducing the carbon footprint of cloud infrastructure, focusing on the integration of green technologies. I analyze the environmental impact of current cloud operations, highlighting key issues such as high energy demand, waste heat, e-waste, and limited renewable energy use. Subsequently, I examine innovative green solutions, including virtualization, energy-efficient hardware, advanced cooling technologies, and the adoption of renewable energy sources. The role of AI is emphasized as a transformative tool for optimizing energy use in data centers through intelligent workload management and AI-driven cooling systems. Furthermore, I discuss challenges in scaling these green technologies globally, addressing regulatory, financial, and technological barriers, and the need for collaboration across sectors. The study concludes with a future outlook on sustainable computing, including promising advancements like fusion energy and AI-managed energy systems, presenting a comprehensive framework for creating sustainable, eco-friendly cloud infrastructure. This framework aims to guide cloud service providers, policymakers, and technology stakeholders toward achieving sustainability goals in the digital economy.

The future internet, 2011

As one of the first worldwide initiatives provisioning ICT (Information and Communication Technologies) services entirely based on renewable energy such as solar, wind and hydroelectricity across Canada and around the world, the GreenStar Network (GSN) is developed to dynamically transport user services to be processed in data centers built in proximity to green energy sources, reducing GHG (Greenhouse Gas) emissions of ICT equipments. Regarding the current approach, which focuses mainly in reducing energy consumption at the micro-level through energy efficiency improvements, the overall energy consumption will eventually increase due to the growing demand from new services and users, resulting in an increase in GHG emissions. Based on the cooperation between Mantychore FP7 and the GSN, our approach is, therefore, much broader and more appropriate because it focuses on GHG emission reductions at the macro-level. Whilst energy efficiency techniques are still encouraged at low-end client equipments, the heaviest computing services are dedicated to virtual data centers powered completely by green energy from a large abundant reserve of natural resources, particularly in northern countries.

International Journal of Advanced Research in Computer Science and Software Engineering, 2013

Green computing, also called green technology, is the environmentally sustainable to use of computers and related resources like-monitors, printer, storage devices, networking and communication systems-efficiently and effectively with minimal or no impact on the environment. Green computing whose goals are to reduce the use of hazardous materials, maximize energy efficiency during the product's lifetime, and promote the recyclability or biodegradability of defunct products and factory waste. Computers today not only used in offices but also at homes. As the number of computers is increasing day by day, so is the amount of electricity consumed by them which in turn is increasing the carbon content in atmosphere. This problem has been realized by people and measures are being taken which help in minimizing the power usage of computers. Therefore , this can be called as Green Computing. We use Green Computing because it-reduced energy usage from green computing techniques translates into lower carbon dioxide emissions, stemming from a reduction in the fossil fuel used in power plants and transportation, Conserving resources means less energy is required to produce, use, and dispose of products ,Saving energy and resources saves money .Green computing even includes changing government policy to encourage recycling and lowering energy use by individuals and businesses.

Global Journal of Engineering and Technology Advances - GJETA, 2025

The meteoric rise of artificial intelligence (AI) has propelled global data center energy consumption to 415 terawatthours in 2024, with projections doubling to 945 TWh by 2030, driven by AI's computational intensity and cooling demands. This review synthesizes cutting-edge solutions for sustainable AI-driven data centers, emphasizing renewable energy (solar, wind, hydropower) and advanced cooling technologies (liquid cooling, immersion cooling, heat reuse). Through global case studies, such as Google's solar-powered facilities, and African innovations, like Kenya's geothermalpowered centers, it showcases scalable integrations reducing energy use by 20-30%. In Africa, where data center capacity grows 25% annually, abundant renewables and water-efficient cooling address high-temperature challenges, yet infrastructure, cost, and equity barriers persist. Future pathways, including eco-friendly coolants and small modular reactors, are proposed alongside policy reforms to ensure net-zero alignment. This article calls for interdisciplinary collaboration to bridge digital divides, offering actionable insights for researchers, industry, and policymakers to drive sustainable AI infrastructure, particularly in Africa's burgeoning digital landscape.

Sigmetrics Performance Evaluation Review, 2010

The large amount of energy consumed by Internet services represents significant and fast-growing financial and environmental costs. Increasingly, services are exploring dynamic methods to minimize energy costs while respecting their service-level agreements (SLAs). Furthermore, it will soon be important for these services to manage their usage of "brown energy" (produced via carbon-intensive means) relative to renewable or "green" energy. This paper introduces a general, optimization-based framework for enabling multi-data-center services to manage their brown energy consumption and leverage green energy, while respecting their SLAs and minimizing energy costs. Based on the framework, we propose policies for request distribution across the data centers. Our policies can be used to abide by caps on brown energy consumption, such as those that might arise from Kyotostyle carbon limits, from corporate pledges on carbon-neutrality, or from limits imposed on services to encourage brown energy conservation. We evaluate our framework and policies extensively through simulations and real experiments. Our results show how our policies allow a service to trade off consumption and cost. For example, using our policies, the service can reduce brown energy consumption by 24% for only a 10% increase in cost, while still abiding by SLAs.

2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2021

Given recent algorithm, software, and hardware innovation, computing has enabled a plethora of new applications. As computing becomes increasingly ubiquitous, however, so does its environmental impact. This paper brings the issue to the attention of computer-systems researchers. Our analysis, built on industry-reported characterization, quantifies the environmental effects of computing in terms of carbon emissions. Broadly, carbon emissions have two sources: operational energy consumption, and hardware manufacturing and infrastructure. Although carbon emissions from the former are decreasing thanks to algorithmic, software, and hardware innovations that boost performance and power efficiency, the overall carbon footprint of computer systems continues to grow. This work quantifies the carbon output of computer systems to show that most emissions related to modern mobile and data-center equipment come from hardware manufacturing and infrastructure. We therefore outline future directions for minimizing the environmental impact of computing systems.

2011

To reduce the negative environmental implications (e.g., CO2 emission and global warming) caused by the rapidly increasing energy consumption, many Internet service operators have started taking various initiatives to operate their cloud-scale data centers with renewable energy. Unfortunately, due to the intermittent nature of renewable energy sources such as wind turbines and solar panels, currently renewable energy is often more expensive than brown energy that is produced with conventional fossil-based fuel. As a result, utilizing renewable energy may impose a considerable pressure on the sometimes stringent operation budgets of Internet service operators. Therefore, two key questions faced by many cloud-service operators are 1) how to dynamically distribute service requests among data centers in different geographical locations, based on the local weather conditions, to maximize the use of renewable energy, and 2) how to do that within their allowed operation budgets. In this paper, we propose GreenWare, a novel middleware system that conducts dynamic request dispatching to maximize the percentage of renewable energy used to power a network of distributed data centers, subject to the desired cost budget of the Internet service operator. Our solution first explicitly models the intermittent generation of renewable energy, e.g., wind power and solar power, with respect to varying weather conditions in the geographical location of each data center. We then formulate the core objective of GreenWare as a constrained optimization problem and propose an efficient request dispatching algorithm based on linear-fractional programming (LFP). We evaluate GreenWare with realworld weather, electricity price, and workload traces. Our experimental results show that GreenWare can significantly increase the use of renewable energy in cloud-scale data centers without violating the desired cost budget, despite the intermittent supplies of renewable energy in different locations and time-varying electricity prices and workloads. Recent years have seen the rapid growth of large and geographically distributed data centers deployed by Internet service operators to support various services

International Research Journal of Multidisciplinary Studies, 2018

With rising energy cost and growing environmental concerns, GREEN COMPUTING is receiving more and more attention. Software and system architectures play a crucial role in both computing and telecommunication systems, and they have been analysed for performance, reliability, maintainability, and security. Yet, little work on analysis based on the amount of energy that the CPU/processor will consume has been reported. Since most communication systems have to run 24/7 (e.g., most server farms, servers in a cloud computing infrastructure), the energy consumption of a system based on a specific software architecture is of great importance. For example, high energy consuming always leads to higher operational cost of the system. High energy consumption also implies more heat produced, thus, more power is required for cooling-down. As the number of computers is increasing day by day, so is the amount of electricity consumed by them which in turn is increasing the carbon content in atmosphe...

Lusitano Caballero Y Verso, 2024

Data centers play a crucial role in the quickly changing digital era. These huge facilities house the fundamental infrastructure of our contemporary data-centric existence, encompassing everything from online social interactions to crucial financial transactions, as well as the operational processes of prominent organizations and governments. Although data centers play a crucial role in facilitating the comforts and progress of our linked society, they often come with a significant environmental burden. As the need for large-scale data storage and processing increases, so does the worry about energy usage, carbon emissions, and sustainability. The purpose of this work, titled "Advancing Data Center Sustainability Through Artificial Intelligence and Renewable Biological Power Sources", is to investigate a revolutionary method for creating environmentally friendly data centers. This publication seeks to provide a thorough overview of the integration of Artificial Intelligence (AI) and renewable biological power sources in data centers. It includes research, case studies, expert analyses, and innovative methodologies. The ultimate goal is to demonstrate how this convergence can contribute to a more sustainable, efficient, and responsible future for data centers worldwide. Link: https://www.lulu.com/shop/alberto-de-miranda/advancing-data-center-sustainability/ebook/product-v89d9w8.html?page=1&pageSize=4

The power consumption of Information and Communication Technology (ICT) is still increasing. In order to handle this problem, we can hereby distinguish between two directions: Green IT and Green by IT. Green IT means, how ICT itself can be more energy efficient. Green by IT means how we can improve energy efficiency in other fields with the help of ICT. In our paper we describe an approach regarding Green IT: How software and especially websites can be improved on the server side regarding their energy consumption. For example, caching and compression technologies, as well as decreased sizes of pictures can significantly reduce the network traffic. Here we give some suggestions and we present concrete measurement results, which show the differences in the induced energy consumption.