{"title":"面向普适计算qos感知的发布者端事件过滤","authors":"Kyungrae Cho, Sung-Keun Song, H. Youn","doi":"10.1109/ICCSA.2007.51","DOIUrl":null,"url":null,"abstract":"In the ubiquitous computing environment a user may interact with a large number of devices. The publish'subscribe paradigm is suitable for the various applications by allowing the subscribers to declare their interests and receive only the notifications of interest. This paper propose a novel event filtering approach preventing waste in the space of the event queue of the event channel due to unwanted events and reducing the network load. Performance evaluation reveals that the proposed scheme displays significant improvement over the existing event service, Java messaging service (JMS) and Omnievent service in terms of event delivery time for various numbers of servers and data sizes.","PeriodicalId":386960,"journal":{"name":"2007 International Conference on Computational Science and its Applications (ICCSA 2007)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Publisher-side Event Filtering for QoS-Awareness in Ubiquitous Computing\",\"authors\":\"Kyungrae Cho, Sung-Keun Song, H. Youn\",\"doi\":\"10.1109/ICCSA.2007.51\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the ubiquitous computing environment a user may interact with a large number of devices. The publish'subscribe paradigm is suitable for the various applications by allowing the subscribers to declare their interests and receive only the notifications of interest. This paper propose a novel event filtering approach preventing waste in the space of the event queue of the event channel due to unwanted events and reducing the network load. Performance evaluation reveals that the proposed scheme displays significant improvement over the existing event service, Java messaging service (JMS) and Omnievent service in terms of event delivery time for various numbers of servers and data sizes.\",\"PeriodicalId\":386960,\"journal\":{\"name\":\"2007 International Conference on Computational Science and its Applications (ICCSA 2007)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Computational Science and its Applications (ICCSA 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSA.2007.51\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computational Science and its Applications (ICCSA 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSA.2007.51","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Publisher-side Event Filtering for QoS-Awareness in Ubiquitous Computing
In the ubiquitous computing environment a user may interact with a large number of devices. The publish'subscribe paradigm is suitable for the various applications by allowing the subscribers to declare their interests and receive only the notifications of interest. This paper propose a novel event filtering approach preventing waste in the space of the event queue of the event channel due to unwanted events and reducing the network load. Performance evaluation reveals that the proposed scheme displays significant improvement over the existing event service, Java messaging service (JMS) and Omnievent service in terms of event delivery time for various numbers of servers and data sizes.