On the average case complexity of some P-complete problems
Parallel approximation to high multiplicity scheduling problems smooth multi-valued quadratic programming
We consider the parallel approximability of two problems arising from high multiplicity scheduling, namely the unweighted model with variable processing requirements and the weighted model with identical processing requirements. These two problems are known to be modelled by a class of quadratic programs that are efficiently solvable in polynomial time. On the parallel setting, both problems are P-complete and hence cannot be efficiently solved in parallel unless P = NC. To deal with the parallel...
Modern approaches to modeling user requirements on resource and task allocation in hierarchical computational grids
Tasks scheduling and resource allocation are among crucial issues in any large scale distributed system, including Computational Grids (CGs). These issues are commonly investigated using traditional computational models and resolution methods that yield near-optimal scheduling strategies. One drawback of such approaches is that they cannot effectively tackle the complex nature of CGs. On the one hand, such systems account for many administrative domains with their own access policies, user privileges,...
On the Average Case Complexity of Some P-complete Problems
We show that some classical P-complete problems can be solved efficiently in NC. The probabilistic model we consider is the sample space of input descriptions of the problem with the underlying distribution being the uniform one. We present parallel algorithms that use a polynomial number of processors and have expected time upper bounded by ( ln 4 + (1))log , asymptotically with high probability, where is the instance size.
Parallel approximation to high multiplicity scheduling problems smooth multi-valued quadratic programming
We consider the parallel approximability of two problems arising from high multiplicity scheduling, namely the and the . These two problems are known to be modelled by a class of quadratic programs that are efficiently solvable in polynomial time. On the parallel setting, both problems are -complete and hence cannot be efficiently solved in parallel unless = . To deal with the parallel approximablity of these problems, we show first a parallel approximation procedure to a subclass of multi-valued...
An application framework to systematically develop complex learning resources based on collaborative knowledge engineering
This contribution proposes software infrastructure to support new types of learning methodologies and resources based on collaborative knowledge engineering by means of an innovative application framework called the virtualized collaborative sessions framework (VCSF). The VCSF helps meet challenging collaborative knowledge engineering requirements in online learning, such as increasing group members' learning performance during the on-line collaborative learning process. In turn, systematic application...
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