• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.10a
• /
• pp.211-212
• /
• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.9
• /
• pp.2573-2589
• /
• 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.

• Journal of Platform Technology
• /
• v.11 no.5
• /
• pp.84-96
• /
• 2023

Network slicing refers to a technology that divides network infrastructure into multiple parts. Network slicing enables flexible network configuration while minimizing the physical resources required for network division. For this reason, network slicing technology has recently been developed and introduced in a form suitable for the 5G environment for efficient management of large-scale network environments. However, systematic analysis of network slicing research in the 5G environment has not been conducted, resulting in a lack of systematic analysis of the technology. Accordingly, in this paper, we provide insight into network slicing technology in the 5G network environment by conducting a comparative analysis of the technology. In this study's comparative analysis, 13 literatures on network slicing in the 5G environment was identified and compared and analyzed through a systematic procedure. As a result of the analysis, three network slicing technologies frequently used for 5G networks were identified: RAN (radio access network) slicing, CN (core network) slicing, and E2E (end-to-end) sliding. These technologies are mainly used for network services. It was confirmed that research is being conducted to achieve quality improvement and network isolation. It is believed that the results of this comparative analysis study can contribute to 6G technology research as a future direction and utilization plan for network slicing research.

• Information and Communications Magazine
• /
• v.33 no.6
• /
• pp.9-17
• /
• 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.

• Journal of Information Processing Systems
• /
• v.16 no.4
• /
• pp.896-914
• /
• 2020

With the rapid growth of network traffic, a large number of connected devices, and higher application services, the traditional network is facing several challenges. In addition to improving the current network architecture and hardware specifications, effective resource management means the development trend of 5G. Although many existing potential technologies have been proposed to solve the some of 5G challenges, such as multiple-input multiple-output (MIMO), software-defined networking (SDN), network functions virtualization (NFV), edge computing, millimeter-wave, etc., research studies in 5G continue to enrich its function and move toward B5G mobile networks. In this paper, focusing on the resource allocation issues of 5G core networks and radio access networks, we address the latest technological developments and discuss the current challenges for resource management in 5G.

• Applied Biological Chemistry
• /
• v.42 no.4
• /
• pp.310-316
• /
• 1999

BBPI contents in domestic soybean and soybean products were investigated by the measurement of chymotrypsin inhibiting activity(C.I.A) and competitive ELISA method. In order to produce polyclonal antibody, BBPI was purified from soybean trypsin-chymotrypsin inhibitor by ion exchange chromatography and electrophoretic gel slicing. Rabbit anti-BBPI polyclonal antibody was produced with the purified BBPI as immunogen. This antibody showed relatively specific binding to BBPI and then used for the establishment of competitive ELISA method to measure BBPI contents in extracts of soybean and soybean products. The standard curve for the measurement of BBPI in soybean extracts was drawn up within the range 0.03 to $30\;{\mu}g/ml$ of BBPI. The C.I.A. and BBPI contents of 12 soybean cultivars were $8,462{\sim}12,428\;U/g$ and $482{\sim}692\;mg%$, respectively. The C.I.A. and BBPI contents were not detected in most of soybean products except soybean sprouts, which contained $10,695{\sim}13,249\;U/g$ of C.I.A. and $529{\sim}803\;mg%$ of BBPI.