{"title":"面向大数据应用的资源优化适应","authors":"Holger Eichelberger, Klaus Schmid","doi":"10.1145/2647908.2655958","DOIUrl":null,"url":null,"abstract":"The resource requirements of Big Data applications may vary dramatically over time, depending on changes in the context. If resources should not be defined for the maximum case, but available resources are mostly static, there is a need to adapt resource usage by modifying the processing behavior. The QualiMaster project researches such an approach for the analysis of systemic risks in the financial markets.","PeriodicalId":339444,"journal":{"name":"Software Product Lines Conference","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Resource-optimizing adaptation for big data applications\",\"authors\":\"Holger Eichelberger, Klaus Schmid\",\"doi\":\"10.1145/2647908.2655958\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The resource requirements of Big Data applications may vary dramatically over time, depending on changes in the context. If resources should not be defined for the maximum case, but available resources are mostly static, there is a need to adapt resource usage by modifying the processing behavior. The QualiMaster project researches such an approach for the analysis of systemic risks in the financial markets.\",\"PeriodicalId\":339444,\"journal\":{\"name\":\"Software Product Lines Conference\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software Product Lines Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2647908.2655958\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software Product Lines Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2647908.2655958","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Resource-optimizing adaptation for big data applications
The resource requirements of Big Data applications may vary dramatically over time, depending on changes in the context. If resources should not be defined for the maximum case, but available resources are mostly static, there is a need to adapt resource usage by modifying the processing behavior. The QualiMaster project researches such an approach for the analysis of systemic risks in the financial markets.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
