Challenges and Opportunities of a Vastly Distributed Cloud Computing Infrastructure – In the Context of the Dong Shu Xi Suan (DSXS) Project of China
0
Citation
20
Reference
10
Related Paper
Abstract:
It has been widely recognized that placing cloud data centers near clean energy sources or in cooler environments may reduce the operational cost and carbon footprint. But when the scale of the system, in terms of the overall computing power and territorial coverage, is large, such benefits may be offset by the additional cost of moving data around and the complexity of efficiently utilizing the network and computational resources. In this paper, we discuss the benefits and challenges of a vastly distributed cloud computing infrastructure, in the particular context of the east-west synergized cloud computing project in China, i.e., the Dong Shu Xi Suan Project (DSXS). We discuss the state of art research that are relevant to this topic, and explore the potential technological advances such a project may bring.Keywords:
Carbon Footprint
Footprint
Concrete and steel are considered the main structural building materials in today's construction. A fair amount of carbon footprint known as embodied carbon footprint is released during their extraction to ultimate utilisation in construction activities. However, quantification and evaluation of the embodied carbon footprint from structural materials of various grades was lacking. This study aimed to evaluate the variation in embodied carbon footprint potential when various classes/grades of concrete and steel in six different combinations were adopted during the design and planning phase using life-cycle analysis (LCA). Building information modelling (BIM) was utilised to virtually construct a two-storey conventional office building, and embodied carbon footprints for each of the six models were quantified. The study highlighted that up to 31% of embodied carbon footprint was avoided from the building. Model M1 (G25XS280) yielded the highest whereas model M4 (G35XS460) was the lowest in contribution. The study also concluded that a considerable amount of reduction in carbon footprint is possible simply by adopting different classes of structural construction materials. The results are expected to help the designers to select best combination of structural materials in future.
Carbon Footprint
Footprint
Embodied Energy
Carbon fibers
Building Information Modeling
Cite
Citations (48)
Researchers in France have developed a new open-source tool to help scientists understand and reduce the carbon footprint of their labs.
Carbon Footprint
Footprint
Carbon fibers
Cite
Citations (0)
Extracting building footprints from aerial images is essential for precise urban mapping with photogrammetric computer vision technologies. Existing approaches mainly assume that the roof and footprint of a building are well overlapped, which may not hold in off-nadir aerial images as there is often a big offset between them. In this paper, we propose an offset vector learning scheme, which turns the building footprint extraction problem in off-nadir images into an instance-level joint prediction problem of the building roof and its corresponding "roof to footprint" offset vector. Thus the footprint can be estimated by translating the predicted roof mask according to the predicted offset vector. We further propose a simple but effective feature-level offset augmentation module, which can significantly refine the offset vector prediction by introducing little extra cost. Moreover, a new dataset, Buildings in Off-Nadir Aerial Images (BONAI), is created and released in this paper. It contains 268,958 building instances across 3,300 aerial images with fully annotated instance-level roof, footprint, and corresponding offset vector for each building. Experiments on the BONAI dataset demonstrate that our method achieves the state-of-the-art, outperforming other competitors by 3.37 to 7.39 points in F1-score. The codes, datasets, and trained models are available at https://github.com/jwwangchn/BONAI.git.
Footprint
Aerial imagery
Nadir
Aerial image
Memory footprint
Cite
Citations (0)
Carbon Footprint
Footprint
Cite
Citations (0)
Based on life cycle assessment, develop carbon footprint assessment methods of wood furniture. By setting of wood furniture carbon footprint evaluation objectives, system boundary, process diagram mapping, data collection and basic formula, calculated the carbon footprint of wood furniture.
Carbon Footprint
Footprint
Carbon fibers
Cite
Citations (3)
The aim of the paper is to quantify the construction production carbon footprint per m3 of the built-up volume of the building. In order to determine the carbon footprint, 5 typical detached houses were selected. The individual buildings have the same material-construction characteristics; however, they differ in the size of the built-up volume, i.e. also in the built-up area. The LCA software was used to quantify the carbon footprint during the production phase of the model houses project. A budget indicator per m3 of the built-up volume was determined based on these calculations.
Carbon Footprint
Footprint
Carbon fibers
Cite
Citations (1)
What Is the Carbon Footprint Controversy? Nearly all humans consume meat, dairy, and egg products in some form. In recent years the environmental movement has touted the necessity of reducing one’s “carbon footprint.” Can we reduce our footprint without changing our diet? Much controversy surrounds...
Carbon Footprint
Footprint
Carbon fibers
Cite
Citations (0)
As the climate change problem becoming an increasingly important global issue, tracking, analyzing and reducing Green House Gas (GHG) emissions at individual user and household level has attracted wide attention. In this paper, we will introduce our approach of building flexible personal carbon footprint calculation platform that can serve as a platform for automatic generation of various carbon footprint calculation and analysis applications.
Carbon Footprint
Footprint
Tracking (education)
Cite
Citations (2)
Carbon Footprint
Open peer review
Footprint
Cite
Citations (0)
With the growing concern for environmental sustainability and the need to mitigate climate change, accurately tracking carbon footprints has become crucial. This paper explores the use of NILM technology for carbon footprint tracking at the household level. A carbon footprint tracking model is proposed based on NILM technology. On this basis, the relationship between carbon footprint and NILM technology is explored. An example is designed to verify the validity of NILM technology in calculating carbon footprint. The simulation results show that the NILM technology can be used to track the carbon footprint at the household. Finally, the paper is summarized.
Carbon Footprint
Footprint
Tracking (education)
Carbon fibers
Cite
Citations (0)