• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.535-538
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• 2011

기반 네트워크 (substrate network)의 자원 여분이 새로 삽입(embed)하고자 하는 가상 네트워크의 자원 요구량을 수용할 수 없을 때, 삽입하고자 하는 가상 네트워크의 요구 자원량을 분할하여 분산 수용함으로써 삽입을 가능케 할 수 있다. 그러나 이러한 작업을 위해서는 각 가상 네트워크의 자원간 상관관계를 꼭 알아야 한다. 이 논문에서 각 가상 네트워크의 명세에 자원 사용 패턴에 있어서의 상관관계를 입력 받음으로써 기반 네트워크의 사용률(utilization)과 가상 네트워크 수용률(acceptance ratio)을 높일 수 있음을 보인다.

• Smart Media Journal
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• v.12 no.11
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• pp.113-124
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• 2023

With the advent of 5G and B5G (Beyond 5G) networks, network virtualization technology that can overcome the limitations of existing networks is attracting attention. The purpose of network virtualization is to provide solutions for efficient network resource utilization and various services. Existing heuristic-based VNE (Virtual Network Embedding) techniques have been studied, but the flexibility is limited. Therefore, in this paper, we propose a GNN-based network slicing classification scheme to meet various service requirements and a RL-based VNE scheme for optimal resource allocation. The proposed method performs optimal VNE using an Actor-Critic network. Finally, to evaluate the performance of the proposed technique, we compare it with Node Rank, MCST-VNE, and GCN-VNE techniques. Through performance analysis, it was shown that the GNN and RL-based VNE techniques are better than the existing techniques in terms of acceptance rate and resource efficiency.

• Journal of KIISE
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• v.44 no.7
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• pp.719-725
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• 2017

To reduce management costs and improve performance, the European Telecommunication Standards Institute (ETSI) introduced the concept of network function virtualization (NFV), which can implement network functions (NFs) on cloud/datacenters. Within the NFV architecture, NFs can share physical resources by hosting NFs on physical nodes (commodity servers). For network service providers who support NFV architectures, an efficient resource allocation method finds utility in being able to reduce operating expenses (OPEX) and capital expenses (CAPEX). Thus, in this paper, we analyzed the network service chain embedding problem via an optimization formulation and found a close-optimal solution based on the Markov approximation framework. Our simulation results show that our approach could increases on average CPU utilization by up to 73% and link utilization up to 53%.