{"title":"用于分散协作边缘计算的功能即服务中间件","authors":"Catarina Gonçalves , José Simão , Luís Veiga","doi":"10.1016/j.future.2025.108069","DOIUrl":null,"url":null,"abstract":"<div><div>Function-as-a-Service (FaaS) emerges as a sophisticated cloud computing paradigm critically suited to processing the exponentially increasing data volumes generated by Internet of Things (IoT) infrastructures. Deploying computational models proximal to data generation sources addresses critical latency and bandwidth constraints inherent in edge-distributed applications. Edge computing environments present complex architectural challenges characterized by large-scale decentralized infrastructures and resource-constrained devices, which substantially impede contemporary Function-as-a-Service implementation strategies. This research introduces FaaS@Edge, a novel framework that leverages volunteered edge node resources discovered through the InterPlanetary File System (IPFS) network and deployed via Apache OpenWhisk. The proposed system addresses computational resource distribution challenges by enabling FaaS runtime deployments across heterogeneous edge infrastructure. Comprehensive experimental evaluation shows that FaaS@Edge introduces marginal latency during function submission while maintaining performance comparable to local OpenWhisk implementations. Empirical results demonstrate request success rates that approximate 98 % for function submission and invocation processes. These findings shows FaaS@Edge’s potential as an efficient computational model for edge computing environments, characterized by low-latency performance and optimized resource allocation.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":"175 ","pages":"Article 108069"},"PeriodicalIF":6.2000,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A function-as-a-service middleware for decentralized collaborative edge computing\",\"authors\":\"Catarina Gonçalves , José Simão , Luís Veiga\",\"doi\":\"10.1016/j.future.2025.108069\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Function-as-a-Service (FaaS) emerges as a sophisticated cloud computing paradigm critically suited to processing the exponentially increasing data volumes generated by Internet of Things (IoT) infrastructures. Deploying computational models proximal to data generation sources addresses critical latency and bandwidth constraints inherent in edge-distributed applications. Edge computing environments present complex architectural challenges characterized by large-scale decentralized infrastructures and resource-constrained devices, which substantially impede contemporary Function-as-a-Service implementation strategies. This research introduces FaaS@Edge, a novel framework that leverages volunteered edge node resources discovered through the InterPlanetary File System (IPFS) network and deployed via Apache OpenWhisk. The proposed system addresses computational resource distribution challenges by enabling FaaS runtime deployments across heterogeneous edge infrastructure. Comprehensive experimental evaluation shows that FaaS@Edge introduces marginal latency during function submission while maintaining performance comparable to local OpenWhisk implementations. Empirical results demonstrate request success rates that approximate 98 % for function submission and invocation processes. These findings shows FaaS@Edge’s potential as an efficient computational model for edge computing environments, characterized by low-latency performance and optimized resource allocation.</div></div>\",\"PeriodicalId\":55132,\"journal\":{\"name\":\"Future Generation Computer Systems-The International Journal of Escience\",\"volume\":\"175 \",\"pages\":\"Article 108069\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2025-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Future Generation Computer Systems-The International Journal of Escience\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167739X25003632\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Generation Computer Systems-The International Journal of Escience","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167739X25003632","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
A function-as-a-service middleware for decentralized collaborative edge computing
Function-as-a-Service (FaaS) emerges as a sophisticated cloud computing paradigm critically suited to processing the exponentially increasing data volumes generated by Internet of Things (IoT) infrastructures. Deploying computational models proximal to data generation sources addresses critical latency and bandwidth constraints inherent in edge-distributed applications. Edge computing environments present complex architectural challenges characterized by large-scale decentralized infrastructures and resource-constrained devices, which substantially impede contemporary Function-as-a-Service implementation strategies. This research introduces FaaS@Edge, a novel framework that leverages volunteered edge node resources discovered through the InterPlanetary File System (IPFS) network and deployed via Apache OpenWhisk. The proposed system addresses computational resource distribution challenges by enabling FaaS runtime deployments across heterogeneous edge infrastructure. Comprehensive experimental evaluation shows that FaaS@Edge introduces marginal latency during function submission while maintaining performance comparable to local OpenWhisk implementations. Empirical results demonstrate request success rates that approximate 98 % for function submission and invocation processes. These findings shows FaaS@Edge’s potential as an efficient computational model for edge computing environments, characterized by low-latency performance and optimized resource allocation.
期刊介绍:
Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications.
Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration.
Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.