Data-Mining Virtual Machines for Resource Optimization
http://groups.csail.mit.edu/EVO-DesignOpt/evo.php?n=Site.SysML

Consolidation with virtual machines allows cost savings and offers energy savings and efficiency. However, the challenge is to maximize consolidation while honoring service commitments (often called SLAs or Service Level Agreements). We are addressing this challenge in ways that exploit genetic programming and reinforcement-based machine learning algorithms. We are evaluating whether it is possible to predict impending overload of a virtual machine’s resources and effectively mitigate the situation in a timely way by reallocating resource types which respond at appropriate timescales. This will be added to Data Mining Resources Subject Tracer™. This has been added to Research Resources Subject Tracer™ Information Blog.