{"title":"离散事件控制的集成协调","authors":"J. Sloan, T. Khoshgoftaar","doi":"10.1109/HASE.2011.26","DOIUrl":null,"url":null,"abstract":"An ensemble is a collection of independent processes, each tasked with drawing potentially differing conclusions about the same data. Using Petri nets, this paper formally describes how ensembles are organized and their behavior coordinated to effect distributed discrete event control of an ocean turbine prototype. Compositions, duals, reverses, and cliques formed over known Petri net graphs comprise the building blocks of the proposed ensemble coordination strategy. The behavior of an ensemble of controllers tasked with fault triage are subject to constraints formulated herein. The controller tasked with prognosis and health management (PHM) itself uses an ensemble of classifiers to detect faults. This ensemble is subject to constraints imposed by stream processing, which require a non-blocking form of rendezvous synchronization. Furthermore, results from each classifier must be fused in a manner that rewards that classifier's ability to predict faults. We identify two competing merit schemes -- one based on individual classifier performance and the other on performance of the sub-ensembles to which that classifier participates. Finally, we model check these Petri nets and report their results.","PeriodicalId":403140,"journal":{"name":"2011 IEEE 13th International Symposium on High-Assurance Systems Engineering","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ensemble Coordination for Discrete Event Control\",\"authors\":\"J. Sloan, T. Khoshgoftaar\",\"doi\":\"10.1109/HASE.2011.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An ensemble is a collection of independent processes, each tasked with drawing potentially differing conclusions about the same data. Using Petri nets, this paper formally describes how ensembles are organized and their behavior coordinated to effect distributed discrete event control of an ocean turbine prototype. Compositions, duals, reverses, and cliques formed over known Petri net graphs comprise the building blocks of the proposed ensemble coordination strategy. The behavior of an ensemble of controllers tasked with fault triage are subject to constraints formulated herein. The controller tasked with prognosis and health management (PHM) itself uses an ensemble of classifiers to detect faults. This ensemble is subject to constraints imposed by stream processing, which require a non-blocking form of rendezvous synchronization. Furthermore, results from each classifier must be fused in a manner that rewards that classifier's ability to predict faults. We identify two competing merit schemes -- one based on individual classifier performance and the other on performance of the sub-ensembles to which that classifier participates. Finally, we model check these Petri nets and report their results.\",\"PeriodicalId\":403140,\"journal\":{\"name\":\"2011 IEEE 13th International Symposium on High-Assurance Systems Engineering\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE 13th International Symposium on High-Assurance Systems Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HASE.2011.26\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 13th International Symposium on High-Assurance Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HASE.2011.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An ensemble is a collection of independent processes, each tasked with drawing potentially differing conclusions about the same data. Using Petri nets, this paper formally describes how ensembles are organized and their behavior coordinated to effect distributed discrete event control of an ocean turbine prototype. Compositions, duals, reverses, and cliques formed over known Petri net graphs comprise the building blocks of the proposed ensemble coordination strategy. The behavior of an ensemble of controllers tasked with fault triage are subject to constraints formulated herein. The controller tasked with prognosis and health management (PHM) itself uses an ensemble of classifiers to detect faults. This ensemble is subject to constraints imposed by stream processing, which require a non-blocking form of rendezvous synchronization. Furthermore, results from each classifier must be fused in a manner that rewards that classifier's ability to predict faults. We identify two competing merit schemes -- one based on individual classifier performance and the other on performance of the sub-ensembles to which that classifier participates. Finally, we model check these Petri nets and report their results.