Abstract-Band - Fakultät für Informatik, TU Wien - Technische ...

Michael Starzinger
Exact Garbage Collection for the Cacao Virtual Machine
Studium: Masterstudium Software Engineering & Internet Computing
Betreuer: Ao.Univ.Prof. Dr. Andreas Krall
Every virtual machine capable of executing Java byte-code needs to perform
some sort of automatic memory management, commonly referred to as
garbage collection. However, it is not specified how this garbage collection
process actually has to be performed. So far the Cacao Virtual Machine
(CacaoVM) used a conservative garbage collector that was designed for
uncooperative environments, thus it has been unable to take full advantage
of the information already present in the runtime infrastructure. This
conservative garbage collector was replaced by an exact one, which has been
tailored to the specific needs of a Java Runtime Environment. In the context
of Java several different components of the virtual machine need to be
orchestrated for exact garbage collection to work. The application threads act
as mutators on the heap and need to be prevented from interfering with the
collector. Another central aspect is identifying the actual references which
point into the heap and prevent objects from being collected. These
references are referred to as the root-set and keep objects alive. The actual
collection algorithms are in charge of cleaning up dead objects and
reorganizing the heap, so that free memory is made available again. Those
algorithms have already been researched in depth over the past decades,
exhibiting vastly different characteristics. All of the above aspects need to be
considered from the perspective of a pure Just-In-Time compilation approach
as taken by CacaoVM. Some crucial simplifications, which rely on fallbacks
into an unoptimized interpreter mode, cannot be applied and need to be
revisited in this setting. Special care was taken to allow future development
towards a generational garbage collection approach by providing the
necessary infrastructure.
Michael Vögler
SILCA - Self-Initiative Load Clustering Agents
Studium: Masterstudium Software Engineering & Internet Computing
Betreuerin: Ao.Univ.Prof. Dr. Eva Kühn
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To handle the load of a service more efficiently load clustering can be used to
cluster a set of loads into smaller subsets, where each of this so called clusters
captures a specific aspect of the load. There exist many clustering algorithms
reaching from unintelligent to intelligent ones. However most approaches are
very problem oriented and therefore hard to compare. In this thesis we
propose a generic architectural pattern for a load clustering framework that
allows the plugging of different clustering and classification algorithms.
Furthermore this pattern should ease the selection of the best algorithm for a
certain problem scenario. The presented pattern assumes autonomous