This FIL project in collaboration with Lyon2 University explores the design of machine learning algorithms for predicting energy consumption of large scale clusters of machines.
Avalon members : Laurent Lefevre and Jean-Christophe Mignot + Didier Puzenat (LIRIS, Univ. Lyon2)
Optimizing resource management in a data center is crucial for economic and ecological reasons.
One of the key points is to distribute all virtual machines running on a minimum number of physical servers. With this in mind, we propose to study an optimization problem which is the migration of a set of virtual machines under different constraints in a datacenter. The aim is to determine the best migration sequence for a set of virtual machines from an initial state to a final state, which minimizes the total migration time, with or without intermediate migration. The problem can be modeled by a state graph.
Project in cooperation with LIRIS.