Infrastructure optimization

Abstract: The increasing volume of data being produced, curated, and made available by research infrastructures in the environmental science domain require services that are able to optimize the delivery and staging of data for researchers and other users of scientific data. Specialized data services for managing data life cycle, for creating and delivering data products, and for customized data processing and analysis all play a crucial role in how these research infrastructures serve their communities, and many of these activities are time‐critical—needing to be carried out frequently within specific time windows. We describe our experiences identifying the time‐critical requirements of environmental scientists making use of computational research support environments. We present a microservice‐based infrastructure optimization suite, the Dynamic Real‐Time Infrastructure Planner, used for constructing virtual infrastructures for research applications on demand. We provide a case study whereby our suite is used to optimize runtime service quality for a data subscription service provided by the Euro‐Argo using EGI Federated Cloud and EUDAT's B2SAFE services, and to consider how such a case study relates to other application scenarios.

Abstract: The Alberta oil sands are a significant source of oil production and greenhouse gas emissions, and their importance will grow as the region is poised for decades of growth. We present an integrated framework that simultaneously considers economic and engineering decisions for the capture, transport, and storage of oil sands CO2 emissions. The model optimizes CO2 management infrastructure at a variety of carbon prices for the oil sands industry. Our study reveals several key findings. We find that the oil sands industry lends itself well to development of CO2 trunk lines due to geographic coincidence of sources and sinks. This reduces the relative importance of transport costs compared to nonintegrated transport systems. Also, the amount of managed oil sands CO2 emissions, and therefore the CCS infrastructure, is very sensitive to the carbon price; significant capture and storage occurs only above 110$/tonne CO2 in our simulations. Deployment of infrastructure is also sensitive to CO2 capture decisions and...