{"title":"An Architectural Style for Solving Computationally Intensive Problems on Large Networks","authors":"Yuriy Brun, N. Medvidović","doi":"10.1109/SEAMS.2007.4","DOIUrl":null,"url":null,"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).","PeriodicalId":354701,"journal":{"name":"International Workshop on Software Engineering for Adaptive and Self-Managing Systems (SEAMS '07)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Software Engineering for Adaptive and Self-Managing Systems (SEAMS '07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEAMS.2007.4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 47
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).