Section: Scientific Foundations

Algorithmics

The researches conducted by the Avalon team address both complex applications, coming from service/component composition and more generally organized as workflows, and complex architectures, that are heterogeneous, distributed, shared, and elastic. While some characteristics are classical to parallel and distributed platforms such as Clusters and Grids, new challenges arise because of the increase of complexity of application structures as well as by the elasticity of infrastructures such as Clouds and by the importance of taking into account energy concerns in Supercomputers for example.

Moreover data-intensive applications imply not only to consider computations in a scheduling process but also data movements in a coordinated way.

In such a context, many metrics can be optimized by transformation and/or scheduling algorithms in order to deploy services or applications on resources. Classical ones are the minimization of application completion or turnaround times, the maximization of the resource usage, or taking care of the fairness between applications. But new challenging optimizations are now related to the economical cost of an execution or to its energy efficiency.

Our main challenge is to propose smart transformation and scheduling algorithms that are inherently multi-criteria optimizations. As not all metrics can be simultaneously optimized, the proposed algorithms consider subsets of them: we target at finding efficient trade-offs. Note that our main concern is to design practical algorithms rather than conducting purely theoretical studies as our goal is at implementing the proposed algorithms in actual software environments.

Moreover, in recent years, we have seen the apparition of hardware-based green leverages (on/off, idle modes, dynamic frequency and speed scaling, etc) applied to various kinds of physical resources (CPU, memory, storage and network interconnect). To exploit them, these facilities must be incorporated into middleware software layers (schedulers, resource managers, etc). The Avalon team explores the benefits of such leverages, for example with respect to elasticity, to improve the energy efficiency of distributed applications and services and to limit the energy consumption of platforms. The goal is to provide the needed amount of physical and virtual resources to fulfill the needs of applications. Such provision is greatly influenced by a large set of contextual choices (hardware infrastructures, software, location, etc).