Related papers: Carbon-Aware Microservice Deployment for Optimal U…

The modern datacenter's computing capabilities have far outstripped the applications running within and have become a hidden cost of doing business due to how software is architected and deployed. Resources are over-allocated to monolithic…

Fog computing is a promising computing paradigm in which IoT data can be processed near the edge to support time-sensitive applications. However, the availability of the resources in the computation device is not stable since they may not…

e-Infrastructures have powered the successful penetration of e-services across domains, and form the backbone of the modern computing landscape. e-Infrastructure is a broad term used for large, medium and small scale computing environments.…

Climate change due to increasing carbon emissions by human activities has been identified as one of the most critical threat to Earth. Carbon neutralization, as a key approach to reverse climate change, has triggered the development of new…

Industries are considering the adoption of cloud and edge computing for real-time applications due to current improvements in network latencies and the advent of Fog and Edge computing. Current cloud paradigms are not designed for real-time…

Due to the energy transition, lots of research has been conducted within the last decade on the topics of energy management systems or local energy trading approaches, often on the day-ahead or intraday level. A large majority of these…

The ever increasing adoption of mobile devices with limited energy storage capacity, on the one hand, and more awareness of the environmental impact of massive data centres and server pools, on the other hand, have both led to an increased…

Nowadays, data-centers are largely under-utilized because resource allocation is based on reservation mechanisms which ignore actual resource utilization. Indeed, it is common to reserve resources for peak demand, which may occur only for a…

Modern data centers suffer from a growing carbon footprint due to insufficient support for environmental sustainability. While hardware accelerators and renewable energy have been utilized to enhance sustainability, addressing Quality of…

As machine learning (ML) continues its rapid expansion, the environmental cost of model training and inference has become a critical societal concern. Existing benchmarks overwhelmingly focus on standard performance metrics such as…

At present, a major concern regarding data centers is their extremely high energy consumption and carbon dioxide emissions. However, because of the over-provisioning of resources, the utilization of existing data centers is, in fact,…

Quantifying locational carbon emissions in power grids is crucial for implementing effective carbon reduction strategies for customers relying on electricity. This paper presents a carbon-aware optimal power flow (OPF) framework that…

This paper presents GreenCourier, a novel scheduling framework that enables the runtime scheduling of serverless functions across geographically distributed regions based on their carbon efficiencies. Our framework incorporates an…

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…

Organizations increasingly need to reassess their supply chain strategies in the rapidly modernizing world towards sustainability. This is particularly true in the United States, where supply chains are very extensive and consume a large…

Deploying microservice-based applications (MSAs) on heterogeneous and dynamic Cloud-Edge infrastructures requires balancing conflicting objectives, such as failure resilience, performance, and environmental sustainability. In this article,…

Cloud service providers are distributing data centers geographically to minimize energy costs through intelligent workload distribution. With increasing data volumes in emerging cloud workloads, it is critical to factor in the network costs…

AI data centers are increasingly becoming tightly coupled compute--energy systems, where workload placement, cooling demand, electricity procurement, storage operation, and carbon emissions interact over time. This paper studies…

This paper explores the optimal policy for using an allocated carbon emission budget over time with the objective to maximize profit, by explicitly taking into account present-biased preferences of decision-makers, accounting for…

The rapid growth in demand for HPC systems has led to a rise in carbon footprint, which requires urgent intervention. In this work, we present a comprehensive analysis of the carbon footprint of high-performance computing (HPC) systems,…