Fault Diagnosis in the Network Function Virtualization: A Survey, Taxonomy, and Future Directions

作者：Jiahui Li, Xiaogang Qi, Jiliang Li, Zhou Su, Yuan Su, Lifang Liu · 发表于：IEEE Internet of Things Journal · 年份：2024 · DOI：10.1109/jiot.2024.3362991 · 被引用次数：12 · 研究领域：Software System Performance and Reliability、Software-Defined Networks and 5G、Network Security and Intrusion Detection

The widespread application of ultra-dense and multivariate Internet of Things (IoT) benefits from Network Function Virtualization (NFV) that provides flexible frameworks and effective management. NFV leverages the virtualization technologies to integrate the existing network functions of devices into standard servers, storages, and switches. Then, the network functions are achieved in software form to displace the private, dedicated and closed network devices. However, NFV also brings instability and challenges to the network management where the network dynamics, lack of visibility, and high frequency and abundant types of faults will increase the difficulty. Therefore, diagnosing the faults embedded in the generic NFV framework is crucial for the effective adoption of NFV to the IoT environment and thus ensuring the user services. This paper summarizes the differences and connections of fault diagnosis between the NFV framework and traditional networks, and introduces the challenges faced by NFV. Moreover, we provide a comprehensive survey of the state-of-the-art fault detection methods for the NFV framework. After an in-depth discussion of the fault propagation characteristics, we further present a detailed taxonomy of the fault localization approaches. Finally, we highlight the future research directions to provide ample space for improvement in applying NFV to the IoT environment.