TY - JOUR
T1 - Fault Diagnosis in the Network Function Virtualization
T2 - A Survey, Taxonomy, and Future Directions
AU - Li, Jiahui
AU - Qi, Xiaogang
AU - Li, Jiliang
AU - Su, Zhou
AU - Su, Yuan
AU - Liu, Lifang
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2024/6/1
Y1 - 2024/6/1
N2 - The widespread application of ultradense 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 article 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.
AB - The widespread application of ultradense 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 article 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.
KW - Fault detection
KW - Internet of Things (IoT)
KW - fault diagnosis
KW - fault localization
KW - network function virtualization (NFV)
UR - https://www.scopus.com/pages/publications/85184803288
U2 - 10.1109/JIOT.2024.3362991
DO - 10.1109/JIOT.2024.3362991
M3 - 文章
AN - SCOPUS:85184803288
SN - 2327-4662
VL - 11
SP - 19121
EP - 19142
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 11
ER -