Distributed Placement of Virtual Network Functions in Edge Networks

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Manual deployment and management are becoming overwhelming with the increasing complexity of networks. Automated deployment and management are imperative and can respond to user requirements promptly. This research provides resource allocation models that cooperated with the NFV orchestration engine and improve the network performance.The research focuses on fault tolerances for unknown failures. Two models for static and dynamic scenarios are proposed. The allocation provided by the proposed models ensures the processing ability satisfies the requirements even though there are k failed nodes in the network. The numerical results show that the proposed models reduce the E2E latency between the VNFs and increase the number of accepted requirements ensuring the resiliency of the functions.