Optimizing Service Function Chaining Migration With Explicit Dynamic Path
نویسندگان
چکیده
Network Function Virtualization (NFV) can support customized on- demand network services with flexibility and cost-efficiency. Virtual (VNF) instances need to be scaled out, in, reallocated across the NFV infrastructure (NFVI) avoid a violation of service agreements when traffic changes. However, selecting new placement VNFs for migrating function chain (SFC) is an issue efficient control. We propose two novel integer linear programming (ILP) models approximation algorithms SFC migration maximize cost-efficiency regarding changes demands dynamic routing. The ILP allow us obtain optimal solutions explicit paths. results provided by our proposed heuristic reinforcement learning are close solution. Evaluation carried out real datasets synthetic topologies provide helpful suggestion strategy provider optimize operating cost in long term.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3150352