Section: Overall Objectives
To achieve the vision proposed in Section 2.1 , the Avalon project aims at making progress to four complementary research axes: energy, data, component models, and application scheduling.
Energy Application Profiling and Modelization
Avalon will improve the profiling and modeling of scientific applications with respect to energy consumption. In particular, it will require to improve the tools that measure the energy consumption of applications, virtualized or not, at large scale, so as to build energy consumption models of applications.
Data-intensive Application Profiling, Modeling, and Management
Avalon will improve the profiling, modeling, and management of scientific applications with respect to CPU and data intensive applications. The challenges are to improve the performance prediction of parallel regular applications, to model and simulate (complex) intermediate storage components, and data-intensive applications, and last to deal with data management for hybrid computing infrastructures.
Resource-Agnostic Application Description Model
Avalon will design component-based models to capture the different facets of parallel and distributed applications while being resource agnostic, so that they can be optimized for a particular execution. In particular, the proposed component models will integrate energy and data modeling results.
Application Mapping and Scheduling
Avalon will propose multi-criteria mapping and scheduling algorithms to meet the challenge of automatizing the efficient utilization of resources taking into consideration criteria such as performance (CPU, network, and storage), energy consumption, and security. Avalon will in particular focus on application deployment, workflow applications, and security management in clouds.
All our theoretical results will be validated with software prototypes using applications from different fields of science such as bioinformatics, physics, cosmology, etc. The experimental testbed Grid'5000 will be our platform of choice for experiments.