Improved water shower model for greener data centers

A virtual data center (VDC) is a combination of interconnected virtual servers hosted on a physical data center that hosts multiple such VDCs. This enables efficient sharing of the data center's resources while handling dynamic resource requirements of the clients. The SecondNet architecture (Guo et al. in Proceedings of ACMSIGCOMM conference on data communication, Barcelona, pp 63---74, 2009) realizes this VDC concept and includes a centralized VDC resource-mapping (virtual to physical) algorithm. Fault tolerance is an important requirement in data center-based services, in order to increase reliability and availability. In this paper, we propose a fault tolerance mechanism to handle server failures by efficiently migrating the virtual machines (VMs) hosted on the failed server to a new location. Using our mechanism, it is shown that recovery from all the faults is possible, even for a server utilization of 90 %. In order to reduce the impact of server failures on the VDCs hosted in the data center, we then present a new load balancing scheme based on clustering that efficiently allocates the VDCs on the data center. Using this scheme, we were able to reduce the affected number of VMs per server failure by 63 %, in case of a BCube network of size 625 nodes, and by 86 %, in case of a BCube network of size 1,296 nodes.

<sec><title>Objective</title> The world is still in a phase of rapid industrialization and urbanization. Excessive carbon emissions has become the primary root cause of various urban or even global environmental problems, further impacting human physiological and psychological health. Cities are the largest sources of carbon emissions and are crucial regions for achieving carbon neutrality goals. Urban blue-green infrastructure (UBGI), comprising natural, semi-natural, or artificial green and blue spaces within cities, is considered as the most important carbon sink space in urban areas and has increasingly attracted widespread attention from researchers. However, there are still many unresolved issues regarding the effectiveness of UBGI in carbon sink enhancement and emission reduction: 1) How is the energy efficiency of carbon sink enhancement and emission reduction measured, and what factors influence it? 2) What are the mechanisms and pathways through which UBGI enhances carbon sink and reduces carbon emission? 3) How can UBGI be regulated to better enhance its effectiveness in carbon sink enhancement and emission reduction? 4) What are the limitations and potential directions for future research? This research aims to address these issues and propose scientifically sound planning strategies for UBGI construction to achieve urban carbon neutrality goals. </sec><sec><title>Methods</title> Through literature synthesis and deduction, this research organizes and analyzes the multi-scale measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction, identifies corresponding influencing factors at each scale, and constructs multi-scale planning strategies for UBGI based on the logical framework of “measurement methods–influencing factors – planning strategies”. </sec><sec><title>Results</title> The research proposes UBGI planning strategies across three spatial scales (site, community and urban area), covering three key aspects: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. Based on current research gaps and planning needs, five major research topics are further identified. This research provides a detailed analysis of the measurement methods and influencing factors of UBGI’s efficiency in carbon sink enhancement and emission reduction from three perspectives: Carbon sequestration and sink enhancement, carbon reduction based on temperature reduction (or preservation), and travel-related carbon reduction. The research finds significant differences in the measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction efficiency across different scales. Contradictory results may occur at different scales, and large-scale research often lacks characterization of internal features, leading to unclear mechanisms of influencing factors and obstructing practical planning. Based on the interpretation of UBGI’s mechanisms for carbon sink enhancement and emission reduction at different scales, this research formulates UBGI planning strategies across three spatial scales (site, community, and urban area). These strategies include: 1) At the site scale, for carbon sequestration and sink enhancement – carbon sink at the source, land balance, and ecological design; for emission reduction – symbiosis with buildings and integration into daily life. 2) At the community scale, for carbon sequestration – overall balance of revenue and expenditure, precise positioning, and proper interconnection of the carbon chain; for emission reduction – incorporation of cool islands and co-construction. 3) At the urban area scale, for carbon sequestration – enhancement of ecological space management and establishment of a carbon-safe pattern; for emission reduction – demand-based layout and organic dispersion. Finally, the research proposes five major research topics for the planning of UBGI’s carbon sink enhancement and emission reduction: How to construct unified measurement methods for UBGI’s efficiency in carbon sink enhancement and emission reduction across scales? How to measure UBGI’s efficiency in carbon reduction based on temperature reduction (or preservation) at the site scale? How to integrate the pathways of carbon sink enhancement and emission reduction for a life cycle assessment of UBGI? How to balance UBGI’s carbon sink enhancement and emission reduction with other functions to achieve the optimal layout for comprehensive benefits? How to achieve urban “carbon justice” through UBGI? </sec><sec><title>Conclusion</title> The carbon sink pathway of the strategy framework requires “carbon sink at the source – precise positioning – safe pattern”, and the emission reduction pathway requires “symbiotic integration – co-construction and sharing – organic dispersion”. The key trade-offs between these two pathways at three spatial scales may provide theoretical support and practical guidance for UBGI construction and management. The five major research topics mentioned above may offer valuable assistance for UBGI construction and future research. </sec>

High energy consumption in data center has become a key problem, and the Carbon (CO $$_2$$ ) emissions from data center have serious impacts on environment. To improve traditional performance-energy model and minimize energy consumption in cloud data center, an energy-efficient and QoS-aware (EEQoS) model is developed for virtual resources consolidation. The EEQoS model is designed to investigate the trade-off between energy and QoS. The user’s satisfaction degree and Euclidean distance of resources are also respectively applied to the QoS model and power model. In addition, this EEQoS model is combined with the particle swarm optimization algorithm by setting the power consumption per QoS value as the objective function to consolidate virtual resources in data center. Compared with traditional power model, the proposed model reduces response time by 27.2%, cost by 31.4%, SLA violations by 40.5% and improves throughput by 13.5% on average while increasing less than 3.8% energy consumption during the whole test period.

Global warming continues to be an intimidating factor for environmental protection, and reducing carbon emissions is an effective way to deal with the phenomenon. However, the energy sector is a significant contributor to greenhouse gas emissions. Therefore, investment in environmental regulations and research and development (R&D), is critical for fostering a low-carbon growth model. This study focuses on 30 provinces in China from 2004 to 2019. We used the spatial Durbin model to investigate how the spatial spillover effect of R&D and environmental regulation impacts carbon emissions. In addition, we applied the dynamic threshold panel model to mitigate potential problems of endogeneity. The results reveal that carbon emissions have a considerable spatial correlation in both temporal and spatial dimensions, exhibiting high and low-value accumulation characteristics. Furthermore, the combined effect of R&D intensity, environmental regulation, and energy consumption were found to contribute to the increase in carbon emissions across China's provinces, and they also suggest different influencing mechanisms. The spillover effects of increased carbon emissions in neighboring regions also contribute to the increase in local carbon emissions. The study also found that R&D and stringent environmental regulations measures strongly moderate the link between energy consumption and carbon emissions. In promoting carbon reduction, by breaking the dynamic equilibrium in China, the provincial investment outflow on R&D intensity could be optimized, and the regional levels should focus more on tightening environmental regulatory measures and promoting the development of energy-conserving technologies.

Carbon verification agencies and power enterprises play a crucial role in the process of reducing carbon emissions. Under government regulation, this paper explores the low-carbon behavior of carbon verification agencies and power enterprises, considering factors such as rewards and penalties, reputation, collusion, and costs. We first constructed a carbon emission reduction game model using evolutionary game theory and replicated dynamic equations to analyze the interactions between carbon verification agencies and power enterprises under government oversight. Subsequently, this study used theoretical derivation and numerical simulation to investigate the model’s evolution and the influence of various factors on the system’s evolution results. It is found that, firstly, the carbon emission reduction game between the carbon verification agency and the power enterprises will eventually be stabilized in two states (authentic verification and carbon emission reduction) and (fraudulent verification and no carbon emission reduction), and the specific stabilization of which state is closely related to the selection of the initial values of the parameters. Secondly, within a certain range, increasing the government’s rewards and penalties, increasing the reputation loss of carbon verification agencies and power enterprises, reducing the benefits of collusion between two parties, reducing the cost of low carbon disclosure and emission reduction of power enterprises will help the construction of a cooperative pattern of low carbon emission reduction and authentic supervision of carbon verification agencies.

Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model

Coordinating building electrification with regional grid decarbonization: Comparison of carbon emissions of different scheduling strategies

Virtual Data Center (VDC) embedding has drawn significant attention recently because of the growing need for efficient and flexible means of Data Center (DC) resource allocation. Existing studies on VDC embedding mainly focus on improving DCs' resource utilization. However, an important problem that has not been considered in VDC embedding solutions is the creation of hot spots by excessive heat dissipation and hot air generation from racks in DCs, which have significant adverse effects on energy consumption of the cooling system and IT equipment lifespan. To address this issue, we propose a temperature-aware VDC embedding scheme to avoid hot spots by minimizing the maximum temperature of hot air drawn to each rack. Meanwhile, we also aim to reduce the total power consumption of IT equipment in this scheme. A Mixed Integer Linear Programming (MILP) model and a heuristic algorithm are developed to implement the proposed VDC embedding scheme. Numerical results show that the proposed temperature-aware embedding scheme can significantly outperform a load-balanced embedding scheme in terms of maximum rack temperature, total power consumption of IT equipment, and VDC rejection ratio. Compared with a scheme that focuses only on maximizing IT resource utilization, which we refer to as IT-only energy-efficient scheme, our proposed scheme can significantly reduce maximum rack temperature and VDC rejection ratio while keeping the total power consumption of IT equipment close to that of an IT-only energy-efficient scheme.

How does sponge city construction affect carbon emission from integrated urban drainage system?

PurposeThis study investigates the association between debt overhang and carbon emissions (both direct and indirect emissions) using a sample of US publicly listed firms.Design/methodology/approachThe study applies generalized least squares (GLS) regression analyses to a sample of 2,043 US firm-year observations over a period of 14 years from 2007 to 2020. The methods include contemporaneous effect, lagged effect, alternative measures of carbon emissions and debt overhang, intensive versus non-intensive analysis, channel analysis, firm fixed effects, change analysis, controlling for credit rating analysis, propensity score matching approach, instrumental variable analysis with industry and year fixed effect.FindingsThis study's findings reveal that the debt overhang problem increases carbon emissions. This finding holds when the authors use alternative measures of carbon emissions and debt overhang. The authors find that carbon abatement investment is a channel that is negatively impacted by debt overhang, which in turn increases carbon emissions. This study's results are robust for several endogeneity tests, including firm fixed effects, change analysis, propensity score matching approach and two-stage least squares (2SLS) instrumental variable analysis.Practical implicationsThe outcome of this research has policy implications for several stakeholders, including investors, firms, market participants and regulators. This study's findings offer insights for investors and firms, helping them allocate resources effectively and make financing decisions aimed at reducing carbon emissions. Regulators and policymakers can also use the findings to formulate policies that promote alternative sustainable finance practices.Originality/valueThe outcome of this research is likely to help firms develop their understanding of the debt overhang problem and undertake strategies that yield a significant amount of funding to invest in reducing carbon emissions.

In a rapid urbanization context, socio-economic development has caused large increases in carbon emissions. In this study, various techniques such as cointegration analysis, vector autoregression, and decoupling elastic function methods are applied to analyze the sequential collaborative relationship between economic development and carbon emissions in the process of urbanization in terms of the time-series lag relationship and the decoupling relationship. The main findings are as follows: (1) urbanization and carbon emissions displayed a temporal correlation relation with a lag of order 4, according to stability tests, and (2) the development of urbanization, economic growth, and changes in land use may be responsible for the time lag in carbon emissions. Furthermore, the mechanisms behind the effect of urbanization on carbon emissions are investigated to assist future carbon emissions reduction efforts. (3) From 1990 to 2014, carbon emissions and economic development showed a temporal evolution trend of "weak decoupling-expansionary coupling-weak decoupling" in the Pearl River Delta region, and there was an overall weak decoupling state: carbon emissions increased with growth in economic development, but the emissions growth rate was lower than the speed of economic development. (4) From 1990 to 2014, economic development showed a trend of sustained growth in the Pearl River Delta region, and differences were detected in the decoupling status between carbon emissions and economic development at different times. The overall decoupling status of the nine cities in the region was one of weak decoupling; however, the decoupling index, carbon emissions, and economic development levels displayed differences, whereby cities with high carbon emissions and high economic development levels were not necessarily the cities in which environmental pressures from economic development were the most severe. Our results have important theoretical and practical significance as they clarify the impact of economic development on carbon emissions in the process of urbanization, as well as the carbon emissions reduction work that must be undertaken in urban systems.

The existing literature tends to overlook the trade‐off between the local government's dual goals of achieving economic growth targets and protecting the environment. This study reveals the adverse effects that local governments may have on the environment under the pressure of economic growth, indicating that an increase in regional economic growth targets is associated with an increase in local carbon emissions. Using data from Chinese prefecture‐level cities from 2000 to 2021, we find a 1% increase in the GDP growth target is associated with an increase in carbon emissions per unit of GDP of 1.6%. The mechanism analysis indicates that a higher regional growth target results in the entry of highly polluting new enterprises and a reduction in environmental protection‐related inputs, which consequently leads to an increase in carbon emissions. The implementation of administrative and market‐based policies, including government policy planning and piloting of emission rights, can mitigate the driving effect of growth targets on carbon emissions. This study provides new evidence on the impact of regional economic growth pressures on carbon emissions and serves as an important reference for governments seeking to formulate effective carbon emission reduction policies.

Data center facilities, which house thousands of servers, storage devices and computing hardware, arranged in 2 meter high racks are providing many thermal challenges. Each rack can dissipate 10–15 kW, and with facilities as large as tens of thousands of square feet, the net power dissipated is typically on the order of several MW. The cost to power these facilities alone can be millions of dollars a year, with the cost to provide adequate cooling not far behind. Significant savings can be realized for the end user by improved design methodology of these high power density data centers. The fundamental need for improved characterization is motivated by inadequacies of simple energy balances to identify local ‘hot spots’ and ultimately provide a reliable modeling framework by which the data centers of the future can be designed. Recent attempts in computational fluid dynamics (CFD) modeling of data centers have been based around a simple rack model, either as a uniform heat generator or specified temperature rise across the rack. This desensitizes the solution to variations of heat load and corresponding flow rate needed to cool the servers throughout the rack. Heat generated at the smaller scales (the chip level) produces changes in the larger length scales of the data center. Accurate simulations of these facilities should attempt to resolve the range of length scales present. In this paper, a multi-scale model where each rack is subdivided into a series of sub-models to better mimic the behavior of individual servers inside the data center is proposed. A Reynolds-averaged Navier-Stokes CFD model of a 110 m2 (1,200 ft2) representative data center with the raised floor cooling scheme was constructed around this multi-scale rack model. Each of the 28 racks dissipated 4.23 kW, giving the data center a power density of 1076 W/m2 (100 W/ft2) based on total floor space. Parametric studies of varying heat loads within the rack and throughout the data center were performed to better characterize the interactions of the sub-rack scale heat generation and the data center. Major results include 1) the presence of a nonlinear thermal response in the upper portion of each rack due to recirculation effects and 2) significant changes in the surrounding racks (up to 10% increase in maximum temperature) observed in response to changes in rack flow rate (50% decrease).

Cloud computing has been a cost-efficient paradigm for deploying various applications in datacenters in recent years. Therefore, efficient provisioning for virtual data center (VDC) requests from different service providers (SPs) over physical data centers plays a vital role in improving the quality of service (QoS) and reducing the operational cost of SPs. Therefore, a significant attention has been paid for the VDC provisioning problem. However, few approaches have been proposed for the problem of reliable VDC embedding across multiple data centers, as most of them only consider the problem of VDC mapping within a single data center. In this paper, we study the problem of QoS-aware VDC provisioning across multiple data centers, such that the total bandwidth consumption in the inter-data center backbone network is minimized while satisfying the reliability requirement of each VDC request. We formulate this problem as a mathematical optimization problem by using integer linear programming (ILP) and propose an efficient heuristic algorithm called reliable VDC embedding (RVDCE) algorithm to solve this NP-hard problem. The simulation results show that the proposed algorithm performs better in terms of blocking ratio, CPU resource consumption, and bandwidth consumption of backbone network than the existing solution. In addition, this paper has also incorporated integrated security to minimize security vulnerabilities seen in other similar approaches. Apart from demonstrating how to resolve security challenges in our VDC proposal, cost calculations have been implemented to demonstrate the robustness, resiliency, validity, and effectiveness of the VDC provisioning solution for cloud computing.

In China, there has been a significant increase in carbon emissions in the new era. Therefore, evaluating the influence of industrial structure upgrades and energy structure optimization on reducing carbon emissions is the objective of this research. Based on the provincial panel data of 30 provinces and cities across China from 1997 to 2019, this paper builds up a fixed-effect panel quantile STIRPAT model to investigate the differences in the impact of industrial structure on carbon emission intensity at different quantile levels from the provincial perspective, and as a way of causality test, the mediation effect model is adopted to empirically test the transmission path of “industrial structure upgrading—energy structure optimization—carbon emission reduction”. The research results show that: (1) Both industrial structure upgrades and energy structure optimization have significant inhibitory effects on carbon emissions, and there are regional heterogeneities. (2) The upgrading of industrial structure has a significant positive effect on optimizing energy structure. (3) The upgrading of industrial structure can not only directly restrain carbon emissions but also indirectly have a significant inhibitory effect on carbon emissions by promoting the optimization of energy structure. Based on the above conclusions, corresponding policy recommendations are proposed to provide suggestions for China to achieve the goal of carbon neutrality.