{"title":"具有现场备份的业务功能链的运营商级可用性感知映射","authors":"Jingyuan Fan, Meiling Jiang, C. Qiao","doi":"10.1109/IWQoS.2017.7969152","DOIUrl":null,"url":null,"abstract":"Network Function Virtualization (NFV) is a promising technique to greatly improve the effectiveness and flexibility of network services through a process named Service Function Chain (SFC) mapping, with which network functions (NFs) are deployed over virtualized and shared platforms in data centers. NFV typically requires a higher availability at the carrier grade than conventional cloud-based IT services, provided by native IaaS mechanism, for example. To achieve the high availability, each VNFs in an SFC can be provisioned with sufficient on-site backups. However, having too many backups may greatly decrease the resource utilization. Therefore, an open challenge is to find an effective method to allocate backup resource in order to maximize the number of SFC requests that can be served while meeting their heterogeneous availability requirements. To address this challenge, we first study how to allocate a minimum amount of backup resource for a single SFC request as an integer nonlinear program and provide an optimal solution. Based on the solution, we then propose an online heuristic algorithm for mapping multiple SFC requests with the objective of maximizing the number of SFC requests that can be served. Last but not least, we introduce a novel backup pooling mechanism to further improve the efficiency of backup resource usage. Through simulations, we show that our proposed algorithm can significantly reduce resource consumption due to backups and increase the number of co-existing SFC requests that can be served.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":"{\"title\":\"Carrier-grade availability-aware mapping of Service Function Chains with on-site backups\",\"authors\":\"Jingyuan Fan, Meiling Jiang, C. 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引用次数: 36
摘要
网络功能虚拟化(Network Function Virtualization, NFV)是一种很有前途的技术,它通过SFC (Service Function Chain)映射过程,将网络功能部署在数据中心的虚拟化和共享平台上,极大地提高了网络服务的有效性和灵活性。与传统的基于云的IT服务(例如,由本地IaaS机制提供)相比,NFV通常要求运营商级的可用性更高。为了实现高可用性,可以为SFC中的每个VNFs提供足够的现场备份。但是,备份太多可能会大大降低资源利用率。因此,一个开放的挑战是找到一种有效的方法来分配备份资源,以便在满足异构可用性需求的同时最大限度地服务SFC请求的数量。为了解决这一挑战,我们首先研究了如何为单个SFC请求分配最小数量的备份资源作为整数非线性程序,并提供了最优解决方案。基于该解决方案,我们提出了一种在线启发式算法,用于映射多个SFC请求,目标是最大化可服务的SFC请求数量。最后,我们引入了一种新的备份池机制,进一步提高了备份资源的使用效率。通过仿真,我们表明我们提出的算法可以显著减少由于备份而导致的资源消耗,并增加可服务的共存SFC请求的数量。
Carrier-grade availability-aware mapping of Service Function Chains with on-site backups
Network Function Virtualization (NFV) is a promising technique to greatly improve the effectiveness and flexibility of network services through a process named Service Function Chain (SFC) mapping, with which network functions (NFs) are deployed over virtualized and shared platforms in data centers. NFV typically requires a higher availability at the carrier grade than conventional cloud-based IT services, provided by native IaaS mechanism, for example. To achieve the high availability, each VNFs in an SFC can be provisioned with sufficient on-site backups. However, having too many backups may greatly decrease the resource utilization. Therefore, an open challenge is to find an effective method to allocate backup resource in order to maximize the number of SFC requests that can be served while meeting their heterogeneous availability requirements. To address this challenge, we first study how to allocate a minimum amount of backup resource for a single SFC request as an integer nonlinear program and provide an optimal solution. Based on the solution, we then propose an online heuristic algorithm for mapping multiple SFC requests with the objective of maximizing the number of SFC requests that can be served. Last but not least, we introduce a novel backup pooling mechanism to further improve the efficiency of backup resource usage. Through simulations, we show that our proposed algorithm can significantly reduce resource consumption due to backups and increase the number of co-existing SFC requests that can be served.