Verifiable Sustainability in Data Centers

Sustainability is crucial for combating climate change and protecting our planet. While there are various systems that can pose a threat to sustainability, data centers are particularly significant due to their substantial energy consumption and environmental impact. Although data centers are becoming increasingly accountable to be sustainable, the current practice of reporting sustainability data is often mired with simple green-washing. To improve this status quo, users as well as regulators need to verify the data on the sustainability impact reported by data center operators. To do so, data centers must have appropriate infrastructures in place that provide the guarantee that the data on sustainability is collected, stored, aggregated, and converted to metrics in a secure, unforgeable, and privacy-preserving manner. Therefore, this paper first introduces the new security challenges related to such infrastructure, how it affects operators and users, and potential solutions and research directions for addressing the challenges for data centers and other industry segments

Strategies for improving the sustainability of data centers via energy mix, energy conservation, and circular energy

Information and communication technologies (ICT) are increasingly permeating our daily life and we ever more commit our data to the cloud. Events like the COVID-19 pandemic put an exceptional burden upon ICT. This involves increasing implementation and use of data centers, which increased energy use and environmental impact. The scope of this work is to summarize the present situation on data centers as to environmental impact and opportunities for improvement. First, we introduce the topic, presenting estimated energy use and emissions. Then, we review proposed strategies for energy efficiency and conservation in data centers. Energy uses pertain to power distribution, ICT, and non-ICT equipment (e.g., cooling). Existing and prospected strategies and initiatives in these sectors are identified. Among key elements are innovative cooling techniques, natural resources, automation, low-power electronics, and equipment with extended thermal limits. Research perspectives are identified and estimates of improvement opportunities are mentioned. Finally, we present an overview on existing metrics, regulatory framework, and bodies concerned

Productive Efficiency of Energy-Aware Data Centers

Information technologies must be made aware of the sustainability of cost reduction. Data centers may reach energy consumption levels comparable to many industrial facilities and small-sized towns. Therefore, innovative and transparent energy policies should be applied to improve energy consumption and deliver the best performance. This paper compares, analyzes and evaluates various energy efficiency policies, which shut down underutilized machines, on an extensive set of data-center environments. Data envelopment analysis (DEA) is then conducted for the detection of the best energy efficiency policy and data-center characterization for each case. This analysis evaluates energy consumption and performance indicators for natural DEA and constant returns to scale (CRS). We identify the best energy policies and scheduling strategies for high and low data-center demands and for medium-sized and large data-centers; moreover, this work enables data-center managers to detect inefficiencies and to implement further corrective actions.Universidad de Sevilla 2018/0000052

Modeling A Green Decision Support System for Data Center Sustainability

The objective of this dissertation is developing more energy efficient data centers while focusing on the environment as well as meeting the increasing computing needs. Reliability of data centers will be the number one priority for management; however, the focus will be to implement a design by incorporating free cooling, applying thermal profiling, utilizing data mining, and continuing virtualization to create more efficient green data centers that are good for the environment. Since the fall of 2009, electrical consumption patterns were measured in the main data center for the servers and the air-conditioners at Montclair State University (MSU) to quantify the carbon footprint and the electrical costs. An important outcome of this work is to build a Decision Support System (DSS) for green computing in data centers. A DSS is a computer based application to assist in providing solutions with respect to decision-making to multifaceted problems. In summary, building on our measurements, the objective is to design a DSS for data centers to enhance energy efficiency, reduce the carbon footprint, and promote sustainability science across disciplines

Diffusion Theory and the Sustainability of IS Innovations:A Greener Earth beneath the Clouds

Our world is increasingly conscious of environmental issues. In IT, one concern is that of the legacy IT infrastructure and the need to improve its sustainability. In this paper we argue that the sustainability of any IS innovation will be formally assessed as organizations and individuals consider such innovations for adoption. Therefore we propose an addition to the classic diffusion of innovation factors of a sixth factor, Relative Sustainability. Relative Sustainability can be initially operationalized using the three eco-goals identified by Watson et al, 2010: 1. Eco-efficiency measures whether an IT good or service reduces ecological impacts and resource use and is competitively priced. 2. Eco-effectiveness measures how well an IT innovation has been designed from the beginning to be sustainable. 3. Eco-equity, which measures how well the IT good or service will result in a fair distribution of resources within and between generations. Measuring eco-equity will require predictions about both initial resource use of an IT innovation (e.g., energy consumption), but also longer-term resource issues, such as final disposal of an IT product (are IT components recyclable or biodegradable, or will they pollute the environment?). We consider the case of the diffusion of cloud computing, in particular the establishment of data centers for private and public clouds. Cloud computing is selected because it represents a transformational change in how computing is done on many levels. The replacement of distributed data centers with fewer, centralized data centers delivers eco-efficiency, especially in energy and water savings and toxic disposal. Also, the new improved designs of data centers that employ a mix of technologies (including server virtualization, sensors and next-generation air- and equipment-cooling processes) and services that aid utilization of far less non-renewable resources, offer the promise of eco-equity. Finally, the massive computing power of cloud centers facilitates innovation of sustainable products delivering opportunities for eco-effectiveness

Examining Future Data Center Power Supply Infrastructures

The rapid expansion of data processing in the past few years has created a massive demand for data center installations worldwide, and energy conservation strategies have become crucial. The enormous increase in data center installations and their significant contribution to global energy consumption require the implementing of energy saving techniques and participating in supporting the power grid. This thesis presents an architecture-level review of power distribution systems in data centers, examining AC, DC, and hybrid architectures with a focus on enhancing efficiency and reliability One of the key areas that can be enhanced to improve the overall energy efficiency of data centers and the provision of ancillary services for the grid is the Uninterruptible Power Supplies (UPS). This thesis reviews the current state-of-the-art power supply systems and topologies mainly used in data centers and aims to identify ways to increase the overall energy efficiency of data center power supply systems. Moreover, this work presents a detailed analysis of the power supply losses and proposes systems that can improve the con- version efficiency of UPS systems under various loading conditions. The performance metrics in the data center business need to be more accurate. Therefore, the variety of performance metrics, considering energy efficiency, sustainability, reliability and costs, are analysed in the thesis. The conclusion of the thesis wraps up the findings and provides guidelines for planning the power supply infrastructure for various conditions

Energy-Aware Algorithms for Greening Internet-Scale Distributed Systems Using Renewables

Internet-scale Distributed Systems (IDSs) are large distributed systems that are comprised of hundreds of thousands of servers located in hundreds of data centers around the world. A canonical example of an IDS is a content delivery network (CDN) that delivers content to users from a large global deployment of servers around the world. IDSs consume large amounts of energy and their energy requirements are projected to increase significantly in the future. With carbon emissions from data centers increasing every year, use of renewables to power data centers is critical for the sustainability of data centers and for the environment. In this thesis we design energy-aware algorithms that leverage renewable sources of energy and study their potential to reduce brown energy consumption in IDSs. Firstly, we study the use of renewable solar energy to power IDS data centers. A net-zero IDS produces as much energy from renewables (green energy) as it needs to entirely off-set its energy consumption. We develop effective algorithms to help minimize the number of solar panels provisioned for net-zero IDSs. We empirically evaluate our algorithms using load traces from Akamai\u27s global CDN and solar data from PVWatts. Our results show that for net-zero year, net-zero month, and net-zero week, our optimal algorithm can reduce the number of panels by 36%, 68%, and 82% respectively, thereby making sustainability of IDSs significantly more achievable. IDSs consume a significant amount of energy for cooling their infrastructure. Therefore, next, we study the potential benefits of using open air cooling (OAC) to reduce the energy usage as well as the capital costs incurred by an IDS for cooling. We develop an algorithm to incorporate OAC into the IDS architecture and empirically evaluate its efficacy using extensive work load traces from Akamai\u27s global CDN and global weather data from NOAA. Our results show that by using OAC, a global IDS can extract a 51% cooling energy reduction during summers and a 92% reduction in the winter. Finally, we study the greening potential of combining two contrasting sources of renewable energy, namely solar energy and open air cooling (OAC). OAC involves the use of outside air to cool data centers if the weather outside is sufficiently cold and dry. Therefore OAC is likely to be abundant in colder weather and at night-time. In contrast, solar energy generation is correlated with sunny weather and day-time. Given their contrasting natures, we study whether synthesizing these two renewable sources of energy can yield complementary benefits. Given the intermittent nature of renewable energy, we use energy storage and load shifting to facilitate the use of green energy and study trade-offs in brown energy reduction based on key parameters like battery size, number of solar panels, and radius of load movement. We do a detailed cost analysis, including amortized cost savings as well as a break-even analysis for different energy prices. Our results show that we can significantly reduce brown energy consumption by about 55% to 59% just by combining the two technologies. We can increase our savings further to between 60% to 65% by adding load movement within a radius of 5000kms, and to between 73% to 89% by adding energy storage

Potential value of waste heat energy from data center in Norway

The European Union (EU) has set ambitious climate goals through the European Green Deal, aiming for climate neutrality by 2050. As a result, utilization of waste heat has gained a momentum due to its potential value in society. Data centers are known for their significant power consumption and cooling needs and present an opportunity as a waste heat emitter. This thesis investigates the potential value of waste heat energy from a data center in Norway, with focus on the Green Edge Compute data center in Stavanger. The thesis assessment considers the context of infrastructure and energy grid distribution, aiming to identify sustainable integrated waste heat solutions. Technical feasibility for integrating waste heat from data centers with district heating systems is examined, considering the low output temperature from the data center and the seasonal variations in supply and demand. Key factors such as environmental impact, community development and economy are evaluated to determine the potential value of waste heat utilization. Due to the relatively new nature of waste heat from data centers through liquid medium, the limited availability of data and previous research in this specific field leads to broad and general findings. To assess the potential value of waste heat energy from data centers a comprehensive literature review was conducted, selecting a relevant case study from Norway as primary source. Collecting and analyzing data, evaluating value factors, identifying limitations, and proposing a solution for high value were the main steps to contribute to the understanding and implementation of waste heat utilization. Quantitative research was the main method applied. To enhance nuanced analysis because of lacking test data, a small-scale anonymous qualitative study was performed, discussing with industry experts to gather professional insights. This thesis explores the potential value of waste heat energy from a data center and highlights the significance in achieving energy efficiency, environmental sustainability, and economic benefits. By harnessing waste heat, data centers can reduce their reliance on conventional heating systems, resulting in energy conservation and operational efficiency. Implementing waste heat recovery systems offers advantages such as cost savings, economic growth, and employment possibilities. Integrating waste heat into energy grid systems and promoting collaborative initiatives enhances the value of utilizing waste heat from data centers