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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.22131 |
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| _version_ | 1866912509301096448 |
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| author | Krishnamohan, Theviyanthan Harvey, Paul |
| author_facet | Krishnamohan, Theviyanthan Harvey, Paul |
| contents | Service Function Chains (SFCs) are one of the key enablers in providing programmable computer networks, paving the way for network autonomy. However, this also introduces new challenges, such as resource allocation and optimisation related to their operation, requiring new algorithms to address these challenges. Various tools have been used in the literature to evaluate these algorithms. However, these tools suffer from inaccuracy, low fidelity, unscalability, inflexibility, or additional code requirements. This paper introduces an emulator based on Mininet and Docker for SFCs called OpenRASE. The goal of OpenRASE is to enable the exploration of resource allocation algorithms for SFCs in a dynamic setting, allowing real CPU usage and latency to be measured. We describe the design and implementation of OpenRASE and discuss its characteristics. We also experimentally evaluate two different algorithms to address the SFC resource allocation challenge, including an online Genetic Algorithm, using OpenRASE to show its effectiveness and practicality for dynamic network conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_22131 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | OpenRASE: Service Function Chain Emulation Krishnamohan, Theviyanthan Harvey, Paul Networking and Internet Architecture Distributed, Parallel, and Cluster Computing Neural and Evolutionary Computing Service Function Chains (SFCs) are one of the key enablers in providing programmable computer networks, paving the way for network autonomy. However, this also introduces new challenges, such as resource allocation and optimisation related to their operation, requiring new algorithms to address these challenges. Various tools have been used in the literature to evaluate these algorithms. However, these tools suffer from inaccuracy, low fidelity, unscalability, inflexibility, or additional code requirements. This paper introduces an emulator based on Mininet and Docker for SFCs called OpenRASE. The goal of OpenRASE is to enable the exploration of resource allocation algorithms for SFCs in a dynamic setting, allowing real CPU usage and latency to be measured. We describe the design and implementation of OpenRASE and discuss its characteristics. We also experimentally evaluate two different algorithms to address the SFC resource allocation challenge, including an online Genetic Algorithm, using OpenRASE to show its effectiveness and practicality for dynamic network conditions. |
| title | OpenRASE: Service Function Chain Emulation |
| topic | Networking and Internet Architecture Distributed, Parallel, and Cluster Computing Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2507.22131 |