S. Costache, Tommaso Madonia, A. Tantawi, M. Steinder
{"title":"数据分析云提供商的批量现货市场","authors":"S. Costache, Tommaso Madonia, A. Tantawi, M. Steinder","doi":"10.1145/3127479.3134348","DOIUrl":null,"url":null,"abstract":"Hosting data analytics services is challenging as their workload is often composed of on-line (e.g., interactive or streaming), requiring fast on-demand provisioning, and batch jobs. As workload demand fluctuations lead to varying idle capacity, efficient resource management is difficult, in particular given different provider objectives, e.g., utilization, revenue.","PeriodicalId":20679,"journal":{"name":"Proceedings of the 2017 Symposium on Cloud Computing","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Batch spot market for data analytics cloud providers\",\"authors\":\"S. Costache, Tommaso Madonia, A. Tantawi, M. Steinder\",\"doi\":\"10.1145/3127479.3134348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hosting data analytics services is challenging as their workload is often composed of on-line (e.g., interactive or streaming), requiring fast on-demand provisioning, and batch jobs. As workload demand fluctuations lead to varying idle capacity, efficient resource management is difficult, in particular given different provider objectives, e.g., utilization, revenue.\",\"PeriodicalId\":20679,\"journal\":{\"name\":\"Proceedings of the 2017 Symposium on Cloud Computing\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 Symposium on Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3127479.3134348\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 Symposium on Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3127479.3134348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Batch spot market for data analytics cloud providers
Hosting data analytics services is challenging as their workload is often composed of on-line (e.g., interactive or streaming), requiring fast on-demand provisioning, and batch jobs. As workload demand fluctuations lead to varying idle capacity, efficient resource management is difficult, in particular given different provider objectives, e.g., utilization, revenue.
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