T. Rabl, Kaiwen Zhang, Mohammad Sadoghi, N. Pandey, Aakash Nigam, Chen Wang, H. Jacobsen
{"title":"Solving manufacturing equipment monitoring through efficient complex event processing: DEBS grand challenge","authors":"T. Rabl, Kaiwen Zhang, Mohammad Sadoghi, N. Pandey, Aakash Nigam, Chen Wang, H. Jacobsen","doi":"10.1145/2335484.2335520","DOIUrl":null,"url":null,"abstract":"In this paper, we present an efficient complex event processing system tailored toward monitoring a large-scale setup of manufacturing equipment. In particular, the key challenge in the equipment monitoring is to develop an event-based system for computing complex manufacturing queries coupled with event notifications and event and query result visualization components. Furthermore, we present an experimental evaluation to validate the effectiveness of the proposed solution with respect to both query latency and throughput.","PeriodicalId":92123,"journal":{"name":"Proceedings of the ... International Workshop on Distributed Event-Based Systems. International Workshop on Distributed Event-Based Systems","volume":"372 1","pages":"335-340"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... International Workshop on Distributed Event-Based Systems. International Workshop on Distributed Event-Based Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2335484.2335520","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, we present an efficient complex event processing system tailored toward monitoring a large-scale setup of manufacturing equipment. In particular, the key challenge in the equipment monitoring is to develop an event-based system for computing complex manufacturing queries coupled with event notifications and event and query result visualization components. Furthermore, we present an experimental evaluation to validate the effectiveness of the proposed solution with respect to both query latency and throughput.