{"title":"Research of Context Situation Awareness Technology","authors":"Dian-xi Shi, Zhendong Wu, Bo Ding, H. Yan","doi":"10.1109/ISORCW.2012.22","DOIUrl":null,"url":null,"abstract":"Context situation, which means a snapshot of the status of the real world, is formed by integrating a large amount of contexts collected from various resources. How to get the context situation and use the situation to provide better services is a challenging issue. In this paper, we focused on this challenge on the basis of the mobile cloud computing architecture. An abstract model is proposed in this paper to uniformly collect the context and send them to cloud. A rule-based large-scale context aggregation algorithm is also proposed which utilizes the MapReduce computing paradigm. Finally, a large-scale context management framework based on the abstract model and the context aggregation algorithm is proposed, and a real-time traffic demo is implemented to verify the validity of the framework.","PeriodicalId":408357,"journal":{"name":"2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISORCW.2012.22","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Context situation, which means a snapshot of the status of the real world, is formed by integrating a large amount of contexts collected from various resources. How to get the context situation and use the situation to provide better services is a challenging issue. In this paper, we focused on this challenge on the basis of the mobile cloud computing architecture. An abstract model is proposed in this paper to uniformly collect the context and send them to cloud. A rule-based large-scale context aggregation algorithm is also proposed which utilizes the MapReduce computing paradigm. Finally, a large-scale context management framework based on the abstract model and the context aggregation algorithm is proposed, and a real-time traffic demo is implemented to verify the validity of the framework.