Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Experimental performance studies on computer systems, including Grids, require deep understandings on their workload characteristics. The need arises from two important and closel...
We consider systems of tandem blocking queues having a common retrial queue. The model represents dynamics of short TCP transfers in the Internet. Analytical results are available...
Spatio-temporal network is defined by a set of nodes, and a set of edges, where the properties of nodes and edges may vary over time. Such networks are encountered in a variety of...
: As data and services are increasingly distributed in the network, rather than stored in a fixed location, one can imagine a scenario in which the Personal Computer, intended as a...