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Fault Tolerance Using an SDN Pattern Framework

Petroulakis, N. E., Spanoudakis, G. & Askoxylakis, Y. (2018). Fault Tolerance Using an SDN Pattern Framework. In: GLOBECOM 2017 - 2017 IEEE Global Communications Conference. IEEE Global Communications Conference 2017, 4-8 Dec 2017, Singapore. doi: 10.1109/GLOCOM.2017.8254082


Software Defined Networking (SDN) and Network Function Virtualization (NFV) are a promising combination for programmable connectivity, rapid service provisioning and service chaining as they offer the necessary end-to-end optimizations. However, with the actual exponential growth of connected devices, future networks such as SDN/NFV require an open-solutions architecture, facilitated by standards and a strong ecosystem. Such networks need to support communication services that offers guarantees about fault tolerance, redundancy, resilience and security. The construction of complex networks preserving Security and Dependability (S&D) properties is necessary to avoid system vulnerabilities, which may occur in the various layers of SDN architectures. In this work, we propose a pattern framework build in an SDN controller able to import design patterns in a rule-based language in order to provide fault tolerance in SDN networks. To evaluate the importance and the functionality of this framework, fault tolerance patterns are proposed to guarantee network connectivity, detection and restoration of network traffic in SDN network infrastructures.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science
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