{"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.
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.