相关论文: A Guide to Reducing Carbon Emissions through Data …

Data centers are large electricity consumers due to the high consumption needs of servers and their cooling systems. Given the current crypto-currency and artificial intelligence trends, the data center electricity demand is bound to grow…

Geographical load balancing can optimize the utilization of green energy and the cost of electricity by taking the advantages of green and price diversities at geographical dispersed data centers. However, higher green energy utilization or…

The proliferation of latency-critical and compute-intensive edge applications is driving increases in computing demand and carbon emissions at the edge. To better understand carbon emissions at the edge, we analyze granular carbon intensity…

To reduce their environmental impact, cloud datacenters' are increasingly focused on optimizing applications' carbon-efficiency, or work done per mass of carbon emitted. To facilitate such optimizations, we present Carbon Containers, a…

The rapid increase in computing demand and its corresponding energy consumption have focused attention on computing's impact on the climate and sustainability. Prior work proposes metrics that quantify computing's carbon footprint across…

Due to growing population and technological advances, global electricity consumption, and consequently also CO2 emissions are increasing. The residential sector makes up 25% of global electricity consumption and has great potential to…

Detailed scheduling has traditionally been optimized for the reduction of makespan and manufacturing costs. However, growing awareness of environmental concerns and increasingly stringent regulations are pushing manufacturing towards…

This letter proposes a market-clearing-based locational marginal carbon emission (LMCE) metric to assess the marginal carbon emission effect of nodal load demand. Unlike the prevalent carbon emission flow (CEF) method that relies on a…

Cloud providers are adapting datacenter (DC) capacity to reduce carbon emissions. With hyperscale datacenters exceeding 100 MW individually, and in some grids exceeding 15% of power load, DC adaptation is large enough to harm power grid…

The carbon footprint of algorithms must be measured and transparently reported so computer scientists can take an honest and active role in environmental sustainability. In this paper, we take analyses usually applied at the industrial…

In this paper, we investigate the potential of spatial and temporal cloud workload shifting to reduce carbon, water, and land use footprints. Specifically, we perform a simulation study leveraging publicly available data on the cloud…

Data centers (DCs) are emerging as large, geographically distributed, controllable loads whose participation in electricity markets can significantly affect grid operation, especially when cloud platforms shift workloads across sites to…

Today's cloud data centers are often distributed geographically to provide robust data services. But these geo-distributed data centers (GDDCs) have a significant associated environmental impact due to their increasing carbon emissions and…

The rapid development of renewable energy in the energy Internet is expected to alleviate the increasingly severe power problem in data centers, such as the huge power costs and pollution. This paper focuses on the eco-friendly power cost…

The global energy landscape is undergoing a profound transformation, often referred to as the energy transition, driven by the urgent need to mitigate climate change, reduce greenhouse gas emissions, and ensure sustainable energy supplies.…

Data centers owned and operated by large companies have a high power consumption and this is expected to increase in the future. However, the ability to shift computing loads geographically and in time can provide flexibility to the power…

Large data centers are being deployed in the U.S. at an unprecedented rate, introducing significant flexible load potential. A portion of data center workloads - best-effort (BE) jobs - can be scheduled flexibly to reduce power system…

Carbon-aware schedulers aim to reduce the operational carbon footprint of data centers by running flexible workloads during periods of low carbon intensity. Most schedulers treat workloads as single monolithic tasks, ignoring that many…

Data centers are growing rapidly, creating the pressing need for the development of critical infrastructure build out to support these resource-intensive large loads. Their immense consumption of electricity and, often, freshwater,…

Global warming is caused by increasing concentrations of greenhouse gases, particularly carbon dioxide (CO2). A metric used to quantify the change in CO2 emissions is the marginal emission factor, defined as the marginal change in CO2…