• Journal of Platform Technology
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• 제11권5호
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• pp.84-96
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• 2023

네트워크 슬라이싱 (network slicing)은 네트워크 인프라를 여러 개로 분할하는 기술을 의미한다. 네트워크 슬라이싱은 네트워크 분할에 들어가는 물리적 자원을 최소화하면서, 유연한 네트워크 구성을 가능하게 한다. 이러한 이유로 최근 네트워크 슬라이싱 기술은 대규모 네트워크 환경의 효율적인 관리를 위해 5G 환경에 적합한 형태로 개발 및 도입되었다. 하지만, 5G 환경에서의 네트워크 슬라이싱 연구에 대한 체계적인 분석이 이루어지고 있지 않아 해당 기술에 대한 체계적인 분석이 부족한 실정이다. 이에 본 논문에서는, 5G 네트워크 환경에서의 네트워크 슬라이싱 기술에 대한 비교 분석을 수행함으로써 해당 기술에 대한 통찰을 제공한다. 본 연구의 비교 분석에서는 체계적인 절차를 통해 5G 환경에서의 네트워크 슬라이싱에 대한 13개의 문헌을 식별하고 비교 분석하였다. 분석 결과, 5G 네트워크를 대상으로 자주 사용되는 3가지 네트워크 슬라이싱 기술인 RAN(radio access network) 슬라이싱, CN(core network) 슬라이싱, E2E(end-to-end) 슬라이딩은 확인하였으며, 이러한 기술은 주로 네트워크 서비스 품질 향상과 네트워크 격리를 달성하기 위해 연구되고 있음을 확인했다. 본 비교 분석 연구 결과는 앞으로의 네트워크 슬라이싱 연구 방향과 활용방안으로서 6G 기술 연구에도 기여할 수 있을 것이라고 판단한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2573-2589
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• 2023

As 5G mobile systems carry multiple services and applications, numerous user, and application types with varying quality of service requirements inside a single physical network infrastructure are the primary problem in constructing 5G networks. Radio Access Network (RAN) slicing is introduced as a way to solve these challenges. This research focuses on optimizing RAN slices within a singular physical cell for vehicle-to-everything (V2X) and enhanced mobile broadband (eMBB) UEs, highlighting the importance of adept resource management and allocation for the evolving landscape of 5G services. We put forth two unique strategies: one being offline network slicing, also referred to as standard network slicing, and the other being Online reinforcement learning (RL) network slicing. Both strategies aim to maximize network efficiency by gathering network model characteristics and augmenting radio resources for eMBB and V2X UEs. When compared to traditional network slicing, RL network slicing shows greater performance in the allocation and utilization of UE resources. These steps are taken to adapt to fluctuating traffic loads using RL strategies, with the ultimate objective of bolstering the efficiency of generic 5G services.

• 정보와 통신
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• 제33권6호
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• pp.9-17
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• 2016

본고에서는 5G 망에서의 서비스 요구사항을 만족하기 위한 구조로서 Network Slicing 구조를 제안하고 세부 적용방안을 기술한다. 이를 위해 5G 서비스를 우선 정의하고 그에 따른 서비스 요구사항을 도출한 후, 이러한 요구사항과 관련해 현재 망의 문제점에 대해 기술하고 망 개선을 위한 기술 요구사항을 정립한다. 특히, 5G에서의 중요성이 높아질 것으로 전망되고 있는 'Network Slicing'의 필요성 및 개념에 대해 서술한다. Network Slicing에 대한 제조사들의 솔루션 동향, 3GPP 등 단체의 표준화 동향, APN 방식의 P-LTE/DECOR/RAN Slicing 등 관련 기술의 발전 동향을 포함한 5G Network Slicing 주요 기술 동향에 대해서 알아본다. 또한, Slice의 관리 및 BSS/OSS등과의 연계를 위한 통신사업자 입장에서의 플랫폼 요구사항을 정리한다. 5G Network Slicing을 충족하기 위한 주요 기술로 C/U plane 분리구조, 범용 서버를 활용한 NFV/SDN, Edge 기반의 분산된 수평적 네트워크, 데이터 오프로딩 및 지연시간 절감을 위한 Edge Computing 등을 들 수 있고 효율적인 자원 관리를 위한 Orchestration 등에 대해서도 알아본다. 이를 기반으로 하여 사업자 입장에서 5G Core Network 기술을 선도함은 물론이고 향후, 조기 상용화를 위한 진화 방향을 제시하고자 한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 추계학술발표대회
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• pp.211-212
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• 2019

Slicing Radio Access Network (RAN) can help in effectively utilizing the network bandwidth and to better manage the increasing traffic over interent. RAN slicing system discussed in this paper is based on an open-source slicing mechanism in which we write a JSON configuration file for slicing policy and send it to the FlexRAN controller. FlexRAN controlls the core networks (CNs) through OAI-RAN on the evolved packet core (EPC) component of this system. Each CN is responsible for handling a saperate RAN slice. The type of internet traffic is identified by the FlexRAN crontroller and is sent to the respective CN through OAI-RAN. CN handles the traffic according to the allocated bandwidth and in this way the internet traffic is sliced inside the EPC component.

• 인터넷정보학회논문지
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• 제23권5호
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.

• Journal of information and communication convergence engineering
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• 제22권3호
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• pp.189-198
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• 2024

This study examined the integrated benefits of 5G New Radio, network slicing, and reinforcement learning (RL) mechanisms in addressing the challenges associated with the increasing proliferation of intelligent objects in communication networks. This study proposed an innovative architecture that initially employed network slicing to efficiently segregate and manage various service types. Subsequently, this architecture was enhanced by applying RL to optimize the subchannel and power allocation strategies. This dual approach was proven through simulation studies conducted in a suburban setting, highlighting the effectiveness of the method for optimizing the use of available frequency bands. The results highlighted significant improvements in mitigating interference and adapting to the dynamic conditions of the network, thereby ensuring efficient dynamic resource allocation. Further, the application of an RL algorithm enabled the system to adjust resources adaptively based on real-time network conditions, thereby proving the flexibility and responsiveness of the scheme to changing network scenarios.

• 인터넷정보학회논문지
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• 제22권5호
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• 한국인터넷방송통신학회논문지
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• 제9권6호
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• pp.9-14
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• 2009

본 논문에서는 단일 주파수 망을 이용하는 AT-DMB 시스템에서의 효율적인 송신기 검출을 위한 확산코드 슬라이싱 기술을 제안하였다. 각 송신 단말기 신호에 상관특성이 좋은 고유의 확산코드를 AT-DMB 프레임의 Null 심벌의 일부에 나누어 할당하고, 수신기에서는 송신 단말기의 고유 코드를 이용하여 다른 단말기의 신호 간섭 상황 하에서도 원하는 신호를 검출하여 수신할 수 있게 한다. 제안된 기법에 의해 얻어진 송신기 정보는 주파수를 효율적으로 사용하기 위한 기술인 SFN 구현을 위해 필요하다. 본 논문의 결과는 무선 디지털 방송 통신 시스템 구현에 적용될 수 있다.

• Journal of information and communication convergence engineering
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• 제17권3호
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• pp.185-190
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• 2019

The explosive growth of data traffic and services has created cost challenges for networks. Studies have attempted to effectively apply network slicing in fifth generation networks to provide high speed, low latency, and various compatible services. However, in network slicing using mixed-integer linear programming, the operation count increases exponentially with the number of physical servers and virtual network functions (VNFs) to be allocated. Therefore, we propose an efficient slice allocation method based on cluster technology, comprising the following three steps: i) clustering physical servers; ii) selecting an appropriate cluster to allocate a VNF; iii) selecting an appropriate physical server for VNF allocation. Solver runtimes of the existing and proposed methods are compared, under similar settings, with respect to intra-slice isolation. The results show that solver runtime decreases, by approximately 30% on average, with an increase in the number of physical servers within the cluster in the presence of intra-slice isolation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.794-815
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• 2023

The rapid development of mobile communication not only has made the industry gradually diversified, but also has enhanced the service quality requirements of users. In this regard, it is imperative to consider jointly network slicing and mobile edge computing. The former mainly ensures the requirements of varied vertical services preferably, and the latter solves the conflict between the user's own energy and harsh latency. At present, the integration of the two faces many challenges and need to carry out at different levels. The main target of the paper is to minimize the energy consumption of the system, and introduce a multi-slice joint task offloading and resource allocation scheme for massive multiple input multiple output enabled heterogeneous networks. The problem is formulated by collaborative optimizing offloading ratios, user association, transmission power and resource slicing, while being limited by the dissimilar latency and rate of multi-slice. To solve it, assign the optimal problem to two sub-problems of offloading decision and resource allocation, then solve them separately by exploiting the alternative optimization technique and Karush-Kuhn-Tucker conditions. Finally, a novel slices task offloading and resource allocation algorithm is proposed to get the offloading and resource allocation strategies. Numerous simulation results manifest that the proposed scheme has certain feasibility and effectiveness, and its performance is better than the other baseline scheme.