Vitri: A framework for environmental decision support on heterogeneous computer networks. Kumar, S.; Doby, T.; Baugh Jr., J.; Brill Jr., E.; and Ranjithan, S. In Bridging the Gap: Meeting the World's Water and Environmental Resources Challenges - Proceedings of the World Water and Environmental Resources Congress 2001, volume 111, 2004.
abstract   bibtex   
Vitri is an object-oriented framework implemented in Java for high-performance distributed computing. Using Vitri, applications can engage in cooperative problem solving by dividing their tasks among heterogeneous clusters of workstations and PCs. Vitri's features include basic support for distributed computing and communication, as well as visual tools for evaluating run-time performance, and modules for heuristic optimization. It balances loads dynamically using a client-side task pool, allows the addition or removal of servers during a run, and provides fault tolerance transparently for servers and networks. Among its more powerful features are modules for heuristic optimization, including an asynchronous global-parallel genetic algorithm that is particularly suited for coarse-grained tasks executing on processors with large variations in processor speeds. By using dataflow techniques, in which computations are explicitly based on the availability and forwarding of data, the usual end-of-generation synchronization points are removed from the algorithm. Results are presented for illustrative applications in water distribution network design and air quality management. Copyright ASCE 2004.
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 title = {Vitri: A framework for environmental decision support on heterogeneous computer networks},
 type = {inProceedings},
 year = {2004},
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 abstract = {Vitri is an object-oriented framework implemented in Java for high-performance distributed computing. Using Vitri, applications can engage in cooperative problem solving by dividing their tasks among heterogeneous clusters of workstations and PCs. Vitri's features include basic support for distributed computing and communication, as well as visual tools for evaluating run-time performance, and modules for heuristic optimization. It balances loads dynamically using a client-side task pool, allows the addition or removal of servers during a run, and provides fault tolerance transparently for servers and networks. Among its more powerful features are modules for heuristic optimization, including an asynchronous global-parallel genetic algorithm that is particularly suited for coarse-grained tasks executing on processors with large variations in processor speeds. By using dataflow techniques, in which computations are explicitly based on the availability and forwarding of data, the usual end-of-generation synchronization points are removed from the algorithm. Results are presented for illustrative applications in water distribution network design and air quality management. Copyright ASCE 2004.},
 bibtype = {inProceedings},
 author = {Kumar, S.V. and Doby, T.A. and Baugh Jr., J.W. and Brill Jr., E.D. and Ranjithan, S.R.},
 booktitle = {Bridging the Gap: Meeting the World's Water and Environmental Resources Challenges - Proceedings of the World Water and Environmental Resources Congress 2001}
}
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