{"title":"Apollo:模块化和分布式运行时系统,用于云、边缘和物联网资源上的无服务器功能组合","authors":"Fedor Smirnov, Behnaz Pourmohseni, T. Fahringer","doi":"10.1145/3452413.3464793","DOIUrl":null,"url":null,"abstract":"This paper provides a first presentation of Apollo, a runtime system for serverless function compositions distributed across the cloud-edge-IoT continuum. Apollo's modular design enables a fine-grained decomposition of the runtime implementation(scheduling, data transmission, etc.) of the application, so that each of the numerous implementation decisions can be optimized separately, fully exploiting the potential for the optimization of the overall performance and costs. Apollo features (a) a flexible model of the application and the available resources and (b) an implementation process based on a large set of independent agents. This flexible structure enables distributing not only the processing, but the implementation process itself across a large number of resources, each running an independent Apollo instance. The ability to flexibly determine the placement of implementation actions opens up new optimization opportunities, while at the same time providing access to greater computing power for optimizing challenging decisions such as task scheduling and the placement and routing of data.","PeriodicalId":339058,"journal":{"name":"Proceedings of the 1st Workshop on High Performance Serverless Computing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Apollo: Modular and Distributed Runtime System for Serverless Function Compositions on Cloud, Edge, and IoT Resources\",\"authors\":\"Fedor Smirnov, Behnaz Pourmohseni, T. Fahringer\",\"doi\":\"10.1145/3452413.3464793\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper provides a first presentation of Apollo, a runtime system for serverless function compositions distributed across the cloud-edge-IoT continuum. Apollo's modular design enables a fine-grained decomposition of the runtime implementation(scheduling, data transmission, etc.) of the application, so that each of the numerous implementation decisions can be optimized separately, fully exploiting the potential for the optimization of the overall performance and costs. Apollo features (a) a flexible model of the application and the available resources and (b) an implementation process based on a large set of independent agents. This flexible structure enables distributing not only the processing, but the implementation process itself across a large number of resources, each running an independent Apollo instance. The ability to flexibly determine the placement of implementation actions opens up new optimization opportunities, while at the same time providing access to greater computing power for optimizing challenging decisions such as task scheduling and the placement and routing of data.\",\"PeriodicalId\":339058,\"journal\":{\"name\":\"Proceedings of the 1st Workshop on High Performance Serverless Computing\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st Workshop on High Performance Serverless Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3452413.3464793\",\"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 1st Workshop on High Performance Serverless Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3452413.3464793","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Apollo: Modular and Distributed Runtime System for Serverless Function Compositions on Cloud, Edge, and IoT Resources
This paper provides a first presentation of Apollo, a runtime system for serverless function compositions distributed across the cloud-edge-IoT continuum. Apollo's modular design enables a fine-grained decomposition of the runtime implementation(scheduling, data transmission, etc.) of the application, so that each of the numerous implementation decisions can be optimized separately, fully exploiting the potential for the optimization of the overall performance and costs. Apollo features (a) a flexible model of the application and the available resources and (b) an implementation process based on a large set of independent agents. This flexible structure enables distributing not only the processing, but the implementation process itself across a large number of resources, each running an independent Apollo instance. The ability to flexibly determine the placement of implementation actions opens up new optimization opportunities, while at the same time providing access to greater computing power for optimizing challenging decisions such as task scheduling and the placement and routing of data.