• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제57차 동계학술대회논문집 26권1호
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• pp.93-94
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• 2018

Software Defined Networking(SDN)은 데이터 부와 컨트롤 부를 나눠 관리하는 혁신적인 방식이다. SDN 환경에서가 아닌 기존의 IP 네트워크에서의 트래픽 분류는 많은 연구가 진행되어 왔다. 트래픽 분류 방법에는 Port 번호를 이용한 트래픽 분류 방법, Payload를 이용한 트래픽 분류 방법, Machine Learning을 이용한 트래픽 분류 방법 등이 있다. 본 논문에서는 Port 번호, Payload, Machine Learning을 이용한 트래픽 분류 방법들을 소개 및 장단점을 설명하고 SDN 환경에서 Machine Learning을 이용한 좀 더 정확한 트래픽 분류 방법을 제안한다.

• 정보과학회 논문지
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• 제44권9호
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• pp.976-985
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• 2017

낮은 비용으로 무선 네트워킹 인프라를 구축할 수 있는 무선 메쉬 네트워크에서는 제한된 무선 자원을 효율적으로 이용하기 위해 패킷 전송(특히, 불필요하게 중복되는 패킷 전송)을 신중하게 처리해야 한다. 본 논문에서는 컨트롤러를 통한 중앙 집중식의 관리가 가능한 소프트웨어 정의 네트워킹 기반의 무선 메쉬 네트워크에서 불필요하게 중복 전송되는 데이터의 양을 감소시키기 위해 경량화된 중복 제거기법을 제안한다. 제안하는 중복 제거 기법은 감소되는 트래픽 양을 극대화하기 위해 컨트롤러가 1) 기계학습 기반의 정보 요청, 2) ID기반의 소스 라우팅, 3) 인기도 기반의 캐쉬 업데이트를 통해 중복 제거 효과를 극대화시킬 수 있는 최적의 경로를 결정한다. 시뮬레이션 결과는 제안하는 기법을 통해 전체 트래픽 부하를 18.34%-48.89% 만큼 감소시킬 수 있음을 보여준다.

• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.9-20
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• 2021

Abstraction applied in computer networking hides network details behind a well-defined representation by building a model that captures an essential aspect of the network system. Two current methods of representation are available, one based on graph theory, where a network node is reduced to a point in a graph, and the other the use of non-methodological iconic depictions such as human heads, walls, towers or computer racks. In this paper, we adopt an abstract representation methodology, the thinging machine (TM), proposed in software engineering to model computer networks. TM defines a single coherent network architecture and topology that is constituted from only five generic actions with two types of arrows. Without loss of generality, this paper applies TM to model the area of network monitoring in packet-mode transmission. Complex network documents are difficult to maintain and are not guaranteed to mirror actual situations. Network monitoring is constant monitoring for and alerting of malfunctions, failures, stoppages or suspicious activities in a network system. Current monitoring systems are built on ad hoc descriptions that lack systemization. The TM model of monitoring presents a theoretical foundation integrated with events and behavior descriptions. To investigate TM modeling's feasibility, we apply it to an existing computer network in a Kuwaiti enterprise to create an integrated network system that includes hardware, software and communication facilities. The final specifications point to TM modeling's viability in the computer networking field.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 춘계학술발표대회
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• pp.200-202
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• 2023

SDN (Software Defined Networking) is an emerging networking system which differs from traditional network architecture. Moreover SDN has many advantages and special capabilities that traditional networks do not have. SDN and P4 are related in that they can be combined to create more advanced and intelligent networking systems. Additionally, Al has emerged as a transformative force in various fields, including SDN. By applying Al and P4 to SDN, network administrators can leverage the power of them to make impact on SDN security. We offer an overview of recent trend of SDN security integrating P4 a nd Al in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권11호
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• pp.5223-5242
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• 2017

In the last decade, the 2.4 GHz band of IEEE 802.11 WLANs has become heavily congested due to the explosive increase in demand of Wi-Fi connectivity. With the current deployment of enterprise WLANs, channel switching mechanism continues to exhibit inefficiencies because it cannot adapt to real-time channel condition and the inability to support seamless channel switching. Software Defined Networking (SDN) as an emerging architecture is promising to introduce flexibility and programmability for wireless network management. Leveraging SDN to existing enterprise WLANs, channel switching method can be improved significantly. This paper presents a software-defined enterprise WLAN framework with a load aware automatic channel switching solution, which utilizes AP load and channel interference factor (CIF) to provide seamless channel switching. Two automatic channel switching algorithms named Single Switch (SS) and Double Switch (DS) are proposed to improve the overall user experience and the experience of users with highest traffic load respectively. Experiment results demonstrate that our solution can efficiently improve user experience in terms of jitter, transmission delay and network throughout when compared to the conventional channel switching mechanism.

• 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.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.303-309
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• 2022

Software Defined Networking (SDN) is a novel approach that have accelerated the development of numerous technologies such as policy-based access control, network virtualization, and others. It allows to boost network architectural flexibility and expedite the return on investment. However, this increases the system's complexity, necessitating the expenditure of dollars to assure the system's security. Network Function Virtualization (NFV) opens up new possibilities for network engineers, but it also raises security concerns. A number of Internet service providers and network equipment manufacturers are grappling with the difficulty of developing and characterizing NFVs and related technologies. Through Moodle's efforts to maintain security, this paper presents a detailed review of security-related challenges in software-defined networks and network virtualization services.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.118-121
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• 2018

끊김 없는 이동성은 멀티미디어가 풍부한 실시간 서비스를 지원하는 미래의 무선 네트워크에서 필수적이다. SDN (Software Defined Networking)은 중앙 집중식 컨트롤러를 통해 무선 네트워크에서 세밀한 플로우 수준의 이동성 관리를 제공할 수 있지만 핸드오버 지연의 새로운 네트워킹 패러다임이다. 스플릿 포인트 방식은 SDN 무선 네트워크에서 핸드오버 및 종단 간 전송 지연을 줄이는 효과적인 방법이다. 스플릿 포인트는 트래픽이 새로운 AP (Access Point)를 향하여 핸드오버 한 후에 기존 플로우 경로상에 존재하는 스위치이다. 본 논문에서는 MN-CN (Corresponding Node) 경로의 각 스위치의 가중치를 스위치와 후보 AP 사이의 평균 고리(홉)로 계산하고 최소 가중치를 갖는 스위치가 스플릿 포인트로 선택된다. 스플릿 포인트 선택 외에도 이 논문은 SDN 에서 제공하는 제어 및 데이터 플레인 분리를 이용하여 핸드오버 후 플로우에 대한 최적의 경로를 복원한다. 제안 아이디어의 수치 해석은 이전 솔루션과 비교하여 총 비용이 9.6 % ~ 13 % 향상되었음을 보여준다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.122-125
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• 2018

최근 다양한 네트워크 서비스에 대한 수요가 증가함에 따라 Service Function (SF)의 동적 구성을 위한 유연한 모델이 요구된다. Service Function Chaining (SFC)은 일련의 SF로 구성된 새로운 네트워크 서비스 배포 모델을 정의한다. Software Defined Networking (SDN)은 제어 평면을 중앙 집중화함으로써 네트워크 트래픽 제어를 단순화하여 SFC동작에 중요한 역할을 한다. SDN 기반 SFC(SD_SFC)는 SF 장애를 감지하기 위한 모니터링 시스템이 필요하다. 그러나 기존의 모니터링 방식은 모든 SF에 Monitoring Agent(MA)를 배치하기 때문에 높은 시그널링 비용을 가진다. 본 논문에서는 최소한의 SF에 MA를 배치함으로써 시그널링 비용을 줄이는 SFC모니터링 방식을 제안한다. 제안하는 SF selection 알고리즘은 최적화된 SF 집합을 사용하여 오버로드된 SF를 반환하여 MA를 배치한다. 우리는 제안 시스템의 효율성을 평가하기 위해 테스트베드 구현을 통해 실험하였다. 실험 결과에 따르면 우리는 기존 방식에 비해서 시그널링 비용을 59.2% 절감하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4678-4702
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• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.