Security-sensitive applications that access and generate large data sets are emerging in various areas such as bioinformatics and high energy physics. Data grids provide data-inte...
In past massively parallel processing systems, such as the TMC CM-5 and the CRI T3E, the scheduling problem consisted of allocating a single type of resource among the waiting job...
The Distributed Probabilistic Protocol (DPP) is a new, approximate algorithm for solving Distributed Constraint Satisfaction Problems (DCSPs) that exploits prior knowledge to impr...
The constraint paradigm provides powerful concepts to represent and solve different kinds of planning problems, e. g. factory scheduling. Factory scheduling is a demanding optimiz...
In distributed real-time systems, meeting the real-time constraints is mandatory but the satisfaction of other application-dependent criteria is most generally required as well. I...