{"title":"Fairness-Aware VNF Mapping and Scheduling in Satellite Edge Networks for Mission-Critical Applications","authors":"Haftay Gebreslasie Abreha;Houcine Chougrani;Ilora Maity;Youssouf Drif;Christos Politis;Symeon Chatzinotas","doi":"10.1109/TNSM.2024.3452031","DOIUrl":null,"url":null,"abstract":"Satellite Edge Computing (SEC) is seen as a promising solution for deploying network functions in orbit to provide ubiquitous services with low latency and bandwidth. Software Defined Networks (SDN) and Network Function Virtualization (NFV) enable SEC to manage and deploy services more flexibly. In this paper, we study a dynamic and topology-aware VNF mapping and scheduling strategy within an SDN/NFV-enabled SEC infrastructure. Our focus is on meeting the stringent requirements of mission-critical (MC) applications, recognizing their significance in both satellite-to-satellite and edge-to-satellite communications while ensuring service delay margin fairness across various time-sensitive service requests. We formulate the VNF mapping and scheduling problem as an Integer Nonlinear Programming problem (\n<monospace>INLP</monospace>\n), with the objective of \n<italic>minimax</i>\n fairness among specified requests while considering dynamic satellite network topology, traffic, and resource constraints. We then propose two algorithms for solving the \n<monospace>INLP</monospace>\n problem: Fairness-Aware Greedy Algorithm for Dynamic VNF Mapping and Scheduling (\n<monospace>FAGD_MASC</monospace>\n) and Fairness-Aware Simulated Annealing-Based Algorithm for Dynamic VNF Mapping and Scheduling (\n<monospace>FASD_MASC</monospace>\n) which are suitable for low and high service arrival rates, respectively. Our extensive simulations demonstrate that both \n<monospace>FAGD_MASC</monospace>\n and \n<monospace>FASD_MASC</monospace>\n approaches are very close to the optimization-based solution and outperform the benchmark solution in terms of service acceptance rates.","PeriodicalId":13423,"journal":{"name":"IEEE Transactions on Network and Service Management","volume":"21 6","pages":"6716-6730"},"PeriodicalIF":4.7000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10659145","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network and Service Management","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10659145/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Satellite Edge Computing (SEC) is seen as a promising solution for deploying network functions in orbit to provide ubiquitous services with low latency and bandwidth. Software Defined Networks (SDN) and Network Function Virtualization (NFV) enable SEC to manage and deploy services more flexibly. In this paper, we study a dynamic and topology-aware VNF mapping and scheduling strategy within an SDN/NFV-enabled SEC infrastructure. Our focus is on meeting the stringent requirements of mission-critical (MC) applications, recognizing their significance in both satellite-to-satellite and edge-to-satellite communications while ensuring service delay margin fairness across various time-sensitive service requests. We formulate the VNF mapping and scheduling problem as an Integer Nonlinear Programming problem (
INLP
), with the objective of
minimax
fairness among specified requests while considering dynamic satellite network topology, traffic, and resource constraints. We then propose two algorithms for solving the
INLP
problem: Fairness-Aware Greedy Algorithm for Dynamic VNF Mapping and Scheduling (
FAGD_MASC
) and Fairness-Aware Simulated Annealing-Based Algorithm for Dynamic VNF Mapping and Scheduling (
FASD_MASC
) which are suitable for low and high service arrival rates, respectively. Our extensive simulations demonstrate that both
FAGD_MASC
and
FASD_MASC
approaches are very close to the optimization-based solution and outperform the benchmark solution in terms of service acceptance rates.
卫星边缘计算(SEC)被视为一种很有前途的解决方案,用于在轨道上部署网络功能,以低延迟和带宽提供无处不在的服务。SDN (Software Defined Networks)和NFV (Network Function Virtualization)技术使SEC能够更加灵活地管理和部署业务。在本文中,我们研究了在支持SDN/ nfv的SEC基础设施中动态和拓扑感知的VNF映射和调度策略。我们的重点是满足关键任务(MC)应用的严格要求,认识到它们在卫星对卫星和边缘对卫星通信中的重要性,同时确保各种时间敏感服务请求的服务延迟裕度公平。我们将VNF映射和调度问题表述为一个整数非线性规划问题(INLP),其目标是在考虑动态卫星网络拓扑结构、流量和资源约束的情况下,在指定请求之间实现最小最大公平性。然后,我们提出了两种解决INLP问题的算法:分别适用于低服务到达率和高服务到达率的基于公平感知的动态VNF映射和调度贪心算法(FAGD_MASC)和基于公平感知的基于模拟退火的动态VNF映射和调度算法(FASD_MASC)。我们的大量模拟表明,FAGD_MASC和FASD_MASC方法都非常接近基于优化的解决方案,并且在服务接受率方面优于基准解决方案。
期刊介绍:
IEEE Transactions on Network and Service Management will publish (online only) peerreviewed archival quality papers that advance the state-of-the-art and practical applications of network and service management. Theoretical research contributions (presenting new concepts and techniques) and applied contributions (reporting on experiences and experiments with actual systems) will be encouraged. These transactions will focus on the key technical issues related to: Management Models, Architectures and Frameworks; Service Provisioning, Reliability and Quality Assurance; Management Functions; Enabling Technologies; Information and Communication Models; Policies; Applications and Case Studies; Emerging Technologies and Standards.