{"title":"复杂事件处理系统中并行处理数据流","authors":"Fuyuan Xiao, Cheng Zhan, Hong Lai, Li Tao","doi":"10.1109/CCDC.2017.7978278","DOIUrl":null,"url":null,"abstract":"For distributed complex event processing systems, handling high volume and continuous data streams with high throughput are required for further decision support. Due to the specific properties of pattern operators, it is difficult to process the data streams in parallel over complex event processing systems. To address the issue, a novel parallel processing strategy is proposed. The proposed method can keep the complex event processing system working stably and continuously via the elapsed time. Finally, the utility of our work is demonstrated through the experiments on the StreamBase system.","PeriodicalId":6588,"journal":{"name":"2017 29th Chinese Control And Decision Conference (CCDC)","volume":"31 1","pages":"6157-6160"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Parallel processing data streams in complex event processing systems\",\"authors\":\"Fuyuan Xiao, Cheng Zhan, Hong Lai, Li Tao\",\"doi\":\"10.1109/CCDC.2017.7978278\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For distributed complex event processing systems, handling high volume and continuous data streams with high throughput are required for further decision support. Due to the specific properties of pattern operators, it is difficult to process the data streams in parallel over complex event processing systems. To address the issue, a novel parallel processing strategy is proposed. The proposed method can keep the complex event processing system working stably and continuously via the elapsed time. Finally, the utility of our work is demonstrated through the experiments on the StreamBase system.\",\"PeriodicalId\":6588,\"journal\":{\"name\":\"2017 29th Chinese Control And Decision Conference (CCDC)\",\"volume\":\"31 1\",\"pages\":\"6157-6160\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 29th Chinese Control And Decision Conference (CCDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC.2017.7978278\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 29th Chinese Control And Decision Conference (CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC.2017.7978278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parallel processing data streams in complex event processing systems
For distributed complex event processing systems, handling high volume and continuous data streams with high throughput are required for further decision support. Due to the specific properties of pattern operators, it is difficult to process the data streams in parallel over complex event processing systems. To address the issue, a novel parallel processing strategy is proposed. The proposed method can keep the complex event processing system working stably and continuously via the elapsed time. Finally, the utility of our work is demonstrated through the experiments on the StreamBase system.