{"title":"基于无服务器边缘计算的模拟应用的联合容器编排和请求路由","authors":"Yong Peng , Miao Zhang , Zhi Zhou , Hao Huang","doi":"10.1016/j.jnca.2025.104284","DOIUrl":null,"url":null,"abstract":"<div><div>Serverless edge computing dynamically invokes functions based on events, enabling on-demand code execution at the network edge and minimizing infrastructure management overhead. This computing paradigm is naturally suitable for event-driven distributed simulation applications, which involves frequent event interactions and stringent latency constraints. When running on top of geographically dispersed edge clouds, container orchestration and request routing have a significant impact on the performance of serverless edge computing-based simulations. In this paper, we propose an online orchestration framework for cross-edge serverless computing-based-simulations, which aims to minimize the resource cost and carbon emission under performance (i.e., latency) constraint, via jointly optimizing the container retention and requesting routing on-the-fly. This long-term cost minimization problem is difficult since it is NP-hard and involves future uncertain information. To simultaneously address these dual challenges, we carefully combine an online optimization technique with an approximate optimization method in a joint optimization framework. This framework first temporally decomposes the long-term time-coupling problem into a series of one-shot fractional problem via Lyapunov optimization, and then applies randomized dependent scheme to round the fractional solution to a near-optimal integral solution. The resulting online algorithm achieves an outstanding performance, as verified by extensive trace-driven simulations.</div></div>","PeriodicalId":54784,"journal":{"name":"Journal of Network and Computer Applications","volume":"243 ","pages":"Article 104284"},"PeriodicalIF":8.0000,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Joint container orchestrating and request routing for serverless edge computing-based simulation applications\",\"authors\":\"Yong Peng , Miao Zhang , Zhi Zhou , Hao Huang\",\"doi\":\"10.1016/j.jnca.2025.104284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Serverless edge computing dynamically invokes functions based on events, enabling on-demand code execution at the network edge and minimizing infrastructure management overhead. This computing paradigm is naturally suitable for event-driven distributed simulation applications, which involves frequent event interactions and stringent latency constraints. When running on top of geographically dispersed edge clouds, container orchestration and request routing have a significant impact on the performance of serverless edge computing-based simulations. In this paper, we propose an online orchestration framework for cross-edge serverless computing-based-simulations, which aims to minimize the resource cost and carbon emission under performance (i.e., latency) constraint, via jointly optimizing the container retention and requesting routing on-the-fly. This long-term cost minimization problem is difficult since it is NP-hard and involves future uncertain information. To simultaneously address these dual challenges, we carefully combine an online optimization technique with an approximate optimization method in a joint optimization framework. This framework first temporally decomposes the long-term time-coupling problem into a series of one-shot fractional problem via Lyapunov optimization, and then applies randomized dependent scheme to round the fractional solution to a near-optimal integral solution. The resulting online algorithm achieves an outstanding performance, as verified by extensive trace-driven simulations.</div></div>\",\"PeriodicalId\":54784,\"journal\":{\"name\":\"Journal of Network and Computer Applications\",\"volume\":\"243 \",\"pages\":\"Article 104284\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2025-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Network and Computer Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S108480452500181X\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Network and Computer Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S108480452500181X","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Joint container orchestrating and request routing for serverless edge computing-based simulation applications
Serverless edge computing dynamically invokes functions based on events, enabling on-demand code execution at the network edge and minimizing infrastructure management overhead. This computing paradigm is naturally suitable for event-driven distributed simulation applications, which involves frequent event interactions and stringent latency constraints. When running on top of geographically dispersed edge clouds, container orchestration and request routing have a significant impact on the performance of serverless edge computing-based simulations. In this paper, we propose an online orchestration framework for cross-edge serverless computing-based-simulations, which aims to minimize the resource cost and carbon emission under performance (i.e., latency) constraint, via jointly optimizing the container retention and requesting routing on-the-fly. This long-term cost minimization problem is difficult since it is NP-hard and involves future uncertain information. To simultaneously address these dual challenges, we carefully combine an online optimization technique with an approximate optimization method in a joint optimization framework. This framework first temporally decomposes the long-term time-coupling problem into a series of one-shot fractional problem via Lyapunov optimization, and then applies randomized dependent scheme to round the fractional solution to a near-optimal integral solution. The resulting online algorithm achieves an outstanding performance, as verified by extensive trace-driven simulations.
期刊介绍:
The Journal of Network and Computer Applications welcomes research contributions, surveys, and notes in all areas relating to computer networks and applications thereof. Sample topics include new design techniques, interesting or novel applications, components or standards; computer networks with tools such as WWW; emerging standards for internet protocols; Wireless networks; Mobile Computing; emerging computing models such as cloud computing, grid computing; applications of networked systems for remote collaboration and telemedicine, etc. The journal is abstracted and indexed in Scopus, Engineering Index, Web of Science, Science Citation Index Expanded and INSPEC.