Solving Anomalies in NFV-SDN Based Service Function Chaining Composition for IoT Network

• Published in: IEEE access Vol. 6; pp. 62286 - 62295
• Main Authors: Zou, Deqing, Huang, Zirong, Yuan, Bin, Chen, Haoyu, Jin, Hai
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Anomalies; Chaining; Composition; Manuals; Monitoring; Network function virtualization; New technology; Policies; policy composition; Redundancy; Security; service function chaining; Software; Software defined network; Software-defined networking; Wide area networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2018.2876314

Service function chaining (SFC) is able to provide customizable network function services to the traffic flows of different IoT subjects. Nowadays, SFC becomes profound to implement the service requirements of different IoT devices with the flexibility and programmability provided by emerging technologies, software defined network (SDN) and network function virtualization . These techniques play an increasingly important role for service deployment and allow the service requirement for certain IoT device to be specified by different subjects, including SDN applications and network managers. However, independent generation of SFC policies by multiple policy makers over the same device may introduce several problems in the process of deploying SFCs to IoT network. Turning the individual considerations into coherent global SFC policies can be challenging. It requires special process of composition and transition, considering the scenario of combining policies with different concerns specified by different entities who have no insight into the policies of others. In this paper, we propose a composition method to solve the anomalies existing in the process of composing distinct policies in the environment of IoT network with multiple IoT service managers. We design two algorithms for the proposed anomaly-free policy composition method, and implement a prototype. Extensive experiment results show that our proposed method can eliminate the anomalies between policies and only induces trivial overhead in the process of generating data plane rules.