This page provides information about the DALHIS research activities.
Research
Results (2016-2017)
The work of the associate team in 2016-2018 centered around two areas: distributed Infrastructure support for workflow and data management and deep partnerships with scientific collaborations. Distributed Infrastructure Support for Workflow and Data Management Energy-efficient data-intensive workflow execution: We explored a way for energy aware HPC cloud users to reduce their footprint on cloud infrastructures …
Results (2013-2015)
The work of the associate team in 2013-2014 centered around three areas: energy efficiency, scientific workflow management, and data life-cycle management in clouds. More precisely, the following results have been achieved. Energy efficiency Performance and energy-efficiency evaluation of Hadoop The exponential growth of scientific and business data has resulted in the evolution of the cloud …
Workplan 2018
Distributed Infrastructure Support for Workflow and Data Management Design of Tools for Dataset Integration (Task 1): Next-generation scientific discoveries are at the boundaries of datasets, e.g., across multiple science disciplines, institutions and spatial and temporal scales. In the context of Deduce and the DALHIS collaboration, we will explore three key research topics. First, our current …
Workplan 2017
Distributed Infrastructure Support for Workflow and Data Management Design of a Cloud Approach for Dataset integration (Task 1): Next-generation scientific discoveries are at the boundaries of datasets, e.g., across multiple science disciplines, institutions and spatial and temporal scales. Today, data integration processes and methods are largely ad-hoc or manual. A generalized resource infrastructure that integrates …
Workplan 2016
1- Distributed Infrastructure Support for Workflow and Data Management We plan to carry on our joint work on workflow management and to initiate a new joint research activity on distributed data integration. Energy-Efficient Data-intensive Workflow Execution: Scientific workflows are composed of many computational tasks, and the dependency among them is represented by task graphs. The …
Workplan 2015
We have identifi ed three major work directions to be investigated as part of DALHIS associated team for 2015: Scienti fic Workows The development of the integrated workfow engine using HOCL and Tigres continues. We recently started to explore the expressiveness of HOCL to express self-adaptive behaviors. Tigres will speci fically focus next year on failure recovery and …
Workplan 2014
Our workplan for 2014 covers three main directions: energy efficiency, scientific workflow management, and data life-cycle management in clouds. Energy efficiency Energy consumption and workload models Infrastructure as a Service (IaaS) clouds provide their customers with virtual machines on demand and self-service following a pay as you go pricing model. Virtual machines are dispatched to …
