{"title":"通过无服务器边缘云支持物联网应用","authors":"I. Wang, Elizabeth Liri, K. Ramakrishnan","doi":"10.1109/CloudNet51028.2020.9335805","DOIUrl":null,"url":null,"abstract":"Cloud computing has grown because of lowered costs due to economies of scale and multiplexing. Serverless computing exploits multiplexing in cloud computing however, for low latency required by IoT applications, the cloud should be moved nearer to the IoT device and the cold start problem should be addressed. Using a real-world dataset, we showed through implementation in an open-source cloud environment based on Knative that a serverless approach to manage IoT traffic is feasible, uses less resources than a serverfull approach and traffic prediction with prefetching can mitigate the cold start delay penalty. However applying the Knative framework directly to IoT traffic without considering the execution context gives unnecessary overhead.","PeriodicalId":156419,"journal":{"name":"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Supporting IoT Applications with Serverless Edge Clouds\",\"authors\":\"I. Wang, Elizabeth Liri, K. Ramakrishnan\",\"doi\":\"10.1109/CloudNet51028.2020.9335805\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud computing has grown because of lowered costs due to economies of scale and multiplexing. Serverless computing exploits multiplexing in cloud computing however, for low latency required by IoT applications, the cloud should be moved nearer to the IoT device and the cold start problem should be addressed. Using a real-world dataset, we showed through implementation in an open-source cloud environment based on Knative that a serverless approach to manage IoT traffic is feasible, uses less resources than a serverfull approach and traffic prediction with prefetching can mitigate the cold start delay penalty. However applying the Knative framework directly to IoT traffic without considering the execution context gives unnecessary overhead.\",\"PeriodicalId\":156419,\"journal\":{\"name\":\"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CloudNet51028.2020.9335805\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudNet51028.2020.9335805","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Supporting IoT Applications with Serverless Edge Clouds
Cloud computing has grown because of lowered costs due to economies of scale and multiplexing. Serverless computing exploits multiplexing in cloud computing however, for low latency required by IoT applications, the cloud should be moved nearer to the IoT device and the cold start problem should be addressed. Using a real-world dataset, we showed through implementation in an open-source cloud environment based on Knative that a serverless approach to manage IoT traffic is feasible, uses less resources than a serverfull approach and traffic prediction with prefetching can mitigate the cold start delay penalty. However applying the Knative framework directly to IoT traffic without considering the execution context gives unnecessary overhead.