Reliability-aware VNF placement using a probability-based approach
Reliability-aware VNF placement using a probability-based approach
复制标题
使用基于概率的方法进行可靠性感知的 VNF 放置
DOI：
10.1109/tnsm.2021.3093199
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
J. Li
中科院分区：
文献类型：
--
作者：
Y. Wu;W. Zheng;Y. Zhang;J. Li
网络功能虚拟化（NFV）是一种新的网络架构理念，可以简化网络服务部署、提高服务管理。然而，网络服务提供商 (NSP) 决定在何处放置虚拟网络功能 (VNF) 是一项挑战。之前的大多数研究仅考虑单链服务，其中请求的 VNF 是按顺序执行的。与以前的方法相比，我们考虑更一般和更实际的情况，其中请求的 VNF 可以并行执行并表示为转发图。我们的目标是通过提供网络服务获得最大利润，同时满足请求的延迟要求。我们将 VNF 放置问题表述为整数线性规划 (ILP) 问题。由于这个问题的复杂性，我们提出了一种称为 PBP 的基于概率的方法，其中 VNF 的放置是根据它们对利润贡献的概率来确定的。此外，我们提出了一种启发式可靠性感知算法来保证服务可靠性，其中请求的每个 VNF 都被分配一个可以与其他请求共享的备份。仿真实验表明，PBP比以前的算法实现了更短的计算时间，同时获得了更高的利润，此外，我们的可靠性感知算法提供了与以前的算法相同的可靠性，同时获得了更高的利润。
Network function virtualization (NFV) is a new network architecture concept that simplifies the deployment of network services and improves service management. However, it is challenging for a network service provider (NSP) to decide where to place virtual network functions (VNFs). Most previous studies have considered only single-chain services, wherein the VNFs for a request are executed in sequence. In contrast to previous approaches, we consider more general and practical situations in which the VNFs of a request can be executed in parallel and are represented as a forwarding graph. Our objective is to maximize the profits earned by providing network services while satisfying the delay requirements of requests. We formulate the VNF placement problem as an integer linear programming (ILP) problem. Due to the complexity of this problem, we propose a probability-based approach called PBP, in which the placements of the VNFs are determined based on their probabilities of contributing to the profit. Furthermore, we propose a heuristic reliability-aware algorithm to guarantee service reliability, in which each VNF of a request is assigned a backup that can be shared with other requests. Simulation experiments show that PBP achieves a much shorter computation time than previous algorithms while earning higher profit, and furthermore, our reliability-aware algorithm provides the same reliability as a previous algorithm while yielding much higher profit.