{"title":"High-Performance Complex Event Processing","authors":"M. Volkova, P. Antonova, A. R. Shameeva","doi":"10.1109/FarEastCon50210.2020.9271338","DOIUrl":null,"url":null,"abstract":"In such areas as transport, healthcare, business process management, financial services, complex event processing (CEP) systems are becoming in demand. Large volumes of streams of events are generated and collected by these systems. Real-time processing of event stream data is essential. Based on current and past events, a decision is made, and forecasting future events is an alternative goal. For the fastest reaction to non-standard behavior, it is necessary to process data streams in real time, it means, as quickly as possible. That's why it is important to find new technologies which can speed up data processing. In this article expensive queries in CEP is identified, effective optimizations to improve their performance significantly is proposed. It is developed and implemented algorithm, which should decrease processing time. The results are compared with state-of-the-art CEP system.","PeriodicalId":280181,"journal":{"name":"2020 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FarEastCon50210.2020.9271338","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In such areas as transport, healthcare, business process management, financial services, complex event processing (CEP) systems are becoming in demand. Large volumes of streams of events are generated and collected by these systems. Real-time processing of event stream data is essential. Based on current and past events, a decision is made, and forecasting future events is an alternative goal. For the fastest reaction to non-standard behavior, it is necessary to process data streams in real time, it means, as quickly as possible. That's why it is important to find new technologies which can speed up data processing. In this article expensive queries in CEP is identified, effective optimizations to improve their performance significantly is proposed. It is developed and implemented algorithm, which should decrease processing time. The results are compared with state-of-the-art CEP system.