Optimizing SDN resource allocation using fuzzy logic and VM mapping technique

Network virtualization refers to running multiple heterogeneous architectures simultaneously on a shared substrate. One major challenge in network virtualization is virtual network mapping to a substrate network. Effective management of substrate network resources during mapping is crucial for optim...

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Bibliographic Details
Published in:Computing 2025, Vol.107 (1), p.13, Article 13
Main Authors: Soltani, Mohammad Amin Zare, Hosseini Seno, Seyed Amin, Mohajerzadeh, AmirHossein
Format: Article
Language:English
Subjects:
Acceptance
Artificial Intelligence
Computer Appl. in Administrative Data Processing
Computer Communication Networks
Computer Science
Fuzzy logic
Information Systems Applications (incl.Internet)
Mapping
Markov chains
Optimization
Productivity
Quality of service
Quality of service architectures
Regular Paper
Resource allocation
Resource management
Simulators
Software
Software Engineering
Software-defined networking
Virtual networks
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Summary:Network virtualization refers to running multiple heterogeneous architectures simultaneously on a shared substrate. One major challenge in network virtualization is virtual network mapping to a substrate network. Effective management of substrate network resources during mapping is crucial for optimizing these resources. Software defined networking (SDN) is a novel technology that separates control logic from data, and is utilized in network virtualization to improve resource management. In this study, we leverage SDN for network virtualization, allowing for dynamic management of substrate resources to achieve optimal mapping. We use a fuzzy Markov model and time slots to optimize response time and improve service quality. The model predicts the appropriate size for sending packets in the next slot and ensures successful mapping, resulting in the most efficient use of network resources. This approach reduces costs and delays, increases acceptance rates, improves quality of service, and ultimately enhances productivity. We use NS2 and Mininet simulators with acceptance rate and latency as evaluation criteria to evaluate our approach. The results indicate a significant improvement over previous research regarding request acceptance rate and time. Specifically, the switch link-resources and acceptance rates show a 7.12% and 9.34% improvement rate, respectively, when compared to SDN-nSR and SDN-NV techniques.
ISSN:0010-485X
1436-5057
DOI:10.1007/s00607-024-01360-4