可靠性感知的边缘计算VNF实例放置
Reliability-aware VNF Instance Placement in Edge Computing
梁晶语 1马博闻 1黄霁崴1
作者信息
- 1. 中国石油大学(北京)石油数据挖掘北京市重点实验室 北京 102249
- 折叠
摘要
为了解决日益增长的延迟敏感型应用程序和用户需求与计算资源受限的冲突,移动边缘计算(Mobile Edge Compu-ting,MEC)已经成为一种很有前途的计算范式.服务提供商通过在边缘环境中部署虚拟化网络功能(Virtual Network Func-tions,VNF),为用户提供更加高效和可扩展性的服务供应链(Service Function Chain,SFC)来满足用户请求.若在提供服务过程中出现不可靠的服务或严重的服务失败,可能导致用户的巨大损失,所以网络服务提供商必须保证提供持续可靠的服务.针对该问题,考虑了边缘服务器的可靠性,利用计算统一设备架构(Computational Unified Device Architecture,CUD A)支持的门控循环单元(Gate Recurrent Unite,GRU)来预测VNF实例是否可用,通过预测结果,提前对VNF进行备份,避免了过度冗余备份造成的成本过高问题.考虑服务器的存储资源有限,提出了基于VNF实例可用性的放置(RVP)算法,优化服务提供商的成本.最后对提出的算法进行了性能评估,实验结果验证了RVP算法的优越性.
Abstract
Mobile edge computing(MEC)has emerged as a promising computing paradigm to solve the conflict between the growing number of latency-sensitive applications and user demands and the constrained computing resources.To provide users with a more efficient and scalability service function chain(SFC)to satisfy users'requests by deploying virtual network functions(VNF)in the edge environment.Unreliable service or serious service failure in the process of providing service may lead to great loss to users,so the network service provider must ensure the provision of constant and reliable service.Considering the reliability of edge servers for this problem,the gate recurrent unit(GRU)supported by computational unified device architecture(CUDA)is used to predict the availability of VNF,and the VNF instances are backed up in advance through the prediction results,avoiding the problem of excessive cost caused by over-redundant backups.The storage resources of the servers are limited,and VNF in-stance availability placement(RVP)algorithm is proposed to optimize the cost of service providers.Finally,performance evalua-tion is performed,and the experimental results show the excellence of the proposed RVP algorithm.
关键词
边缘计算/服务供应链/虚拟化网络功能/可靠性/VNF实例放置Key words
Edge computing/Service function chain/Virtual network function/Reliability/VNF instance placement引用本文复制引用
基金项目
国家自然科学基金(61972414)
北京市科技新星计划(Z201100006820082)
出版年
2024
NETL
NSTL
万方数据