This paper discusses the impact of the hierarchical master-worker paradigm on performance of an application program, which solves an optimization problem by a parallel branch and ...
The Iceberg-Cube problem restricts the computation of the data cube to only those group-by partitions satisfying a minimum threshold condition defined on a specified measure. In t...
The Distributed Probabilistic Protocol (DPP) is a new, approximate algorithm for solving Distributed Constraint Satisfaction Problems (DCSPs) that exploits prior knowledge to impr...
We introduce Bayesian Expansion (BE), an approximate numerical technique for passage time distribution analysis in queueing networks. BE uses a class of Bayesian networks to appro...