by Yuriy Brun, Nenad Medvidovic

Abstract:

Large networks, such as the Internet, pose an ideal medium for solving computationally intensive problems, such as NP-complete problems, yet no well-scaling architecture for computational Internet-sized systems exists. We propose a software architectural style for large networks, based on a formal mathematical study of crystal growth that will exhibit properties of (1) discreetness (nodes on the network cannot learn the algorithm or input of the computation), (2) fault-tolerance (malicious, faulty, and unstable nodes may not break the computation), and (3) scalability (communication among the nodes does not increase with network or problem size).

Citation:

Yuriy Brun and Nenad Medvidovic, An architectural style for solving computationally intensive problems on large networks, in Proceedings of Software Engineering for Adaptive and Self-Managing Systems (SEAMS), 2007 (SEAMS 2020 Most Influential Paper Award).

Bibtex:

@inproceedings{Brun07seams, author = {Yuriy Brun and Nenad Medvidovic}, title = {\href{http://people.cs.umass.edu/brun/pubs/pubs/Brun07seams.pdf}{An architectural style for solving computationally intensive problems on large networks}}, booktitle = {Proceedings of Software Engineering for Adaptive and Self-Managing Systems (SEAMS)}, venue = {SEAMS}, month = {May}, date = {26--27}, year = {2007}, address = {Minneapolis, {MN}, {USA}}, doi = {10.1109/SEAMS.2007.4}, accept = {$\frac{18}{26} \approx 69\%$}, note = {\raisebox{-.5ex}{\includegraphics[height=2.5ex]{trophy}}~SEAMS 2020 Most Influential Paper Award. \href{https://doi.org/10.1109/SEAMS.2007.4}{DOI: 10.1109/SEAMS.2007.4}}, comment = {<span class="emphasis">SEAMS 2020 Most Influential Paper Award</span>}, abstract = {Large networks, such as the Internet, pose an ideal medium for solving computationally intensive problems, such as NP-complete problems, yet no well-scaling architecture for computational Internet-sized systems exists. We propose a software architectural style for large networks, based on a formal mathematical study of crystal growth that will exhibit properties of (1) discreetness (nodes on the network cannot learn the algorithm or input of the computation), (2) fault-tolerance (malicious, faulty, and unstable nodes may not break the computation), and (3) scalability (communication among the nodes does not increase with network or problem size).}, fundedBy = {NSF ITR-0312780}, }