• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5179-5202
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• 2018

Transmission Control Protocol (TCP) is the most widely used protocol in the cloud data centers today. However, cloud data centers using TCP experience many issues as TCP was designed based on the assumption that it would primarily be used in Wide Area Networks (WANs). One of the major issues with TCP in the cloud data centers is the Incast issue. This issue arises because of the many-to-one communication pattern that commonly exists in the modern cloud data centers. In many-to-one communication pattern, multiple senders simultaneously send data to a single receiver. This causes packet loss at the switch buffer which results in TCP throughput collapse that leads to high Flow Completion Time (FCT). Recently, Software-Defined Networking (SDN) has been used by many researchers to mitigate the Incast issue. In this paper, a detailed survey of various SDN based solutions to the Incast issue is carried out. In this survey, various SDN based solutions are classified into four categories i.e. TCP Receive Window based solutions, Tuning TCP Parameters based solutions, Quick Recovery based solutions and Application Layer based solutions. All the solutions are critically evaluated in terms of their principles, advantages, and shortcomings. Another important feature of this survey is to compare various SDN based solutions with respect to different performance metrics e.g. maximum number of concurrent senders supported, calculation of delay at the controller etc. These performance metrics are important for deployment of any SDN based solution in modern cloud data centers. In addition, future research directions are also discussed in this survey that can be explored to design and develop better SDN based solutions to the Incast issue.

• Information and Communications Magazine
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• v.30 no.3
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• pp.67-72
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• 2013

본 고에서는, 미래 인터넷 (Future Internet) 연구에 있어서, 가장 많은 관심과 가능성 예측에 기반한 실제적인 투자를 이끌어 내고 있는 두 개의 주요 핵심 기술 분야인 콘텐츠 중심 네트워킹 (Content-Centric Networking: CCN)과 소프트웨어 정의 네트워킹 기술 (Software-Defined Networking: SDN)의 접목에 대해서, 그 배경과 당위성 그리고 관련 연구 동향을 살펴 본다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.379-386
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• 2014

Recently, middleboxes play a key role in many network settings such as firewalls, VPN gateways, proxies, intrusion detection and prevention systems, and WAN optimizers. However, achieving the performance and security benefits that middleboxes offer is highly complex, and therefore it is essential to manage middleboxes efficiently and dynamically. In this respect, Software-Defined Networking (SDN) offers a promising solution for middlebox policy enforcement by using logically centralized management, decoupling the data and control planes, and providing the ability to programmatically configure forwarding rules. Also, cloud computing and distributed Network Function Virtualization (NFV) can enable to manage middleboxes more easily. We introduce SDN-based middlebox management framework in integrated wired and wireless networks and discuss the further issues.

• ETRI Journal
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• v.40 no.2
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• pp.227-236
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• 2018

Ultra-dense small cell networks (UD-SCNs) have been identified as a promising scheme for next-generation wireless networks capable of meeting the ever-increasing demand for higher transmission rates and better quality of service. However, UD-SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software-defined networking (SDN)-based hierarchical agglomerative clustering (SDN-HAC) framework, which leverages SDN to centrally control all sub-channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non-cooperative scenarios, respectively.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.421-423
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• 2012

새로운 네트워크 아이디어를 검증하기 위해서는 실질적인 대규모 트래픽 상황에서 실험을 거쳐야 한다. 하지만 기존의 네트워크 구조는 네트워크 벤더들에 의해서 제어부분이 개방되지 않은 장치들로 구성 되어 있기 때문에 검증과정에 있어서 어려움을 겪는다. 이러한 문제점을 해결하기 위해 최근 소프트웨어 정의 네트워킹(Software Defined Networking: SDN) 연구가 활발히 진행되고 있다. 그러나 기존의 SDN 연구들은 플로우 테이블에 국한한 제한된 인터페이스만을 정의하고 있고 이러한 이유로 여러 SDN간이나 일반적인 네트워크들까지 통합하여 제어할 수 있는 슈퍼 컨트롤러에 대한 연구가 요구된다. 본 논문에서는 최근 SDN 분야에서 활발히 연구되고 있는 오픈플로우(OpenFlow)를 바탕으로 소프트웨어 정의 네트워킹의 기능 확장을 위한 슈퍼 컨트롤러 설계를 제안한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.43-44
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• 2018

본 논문에서는 SDN환경에서 트래픽 분류를 위한 특징 선택 기법을 제안한다. 최근 들어 다양한 스마트폰 어플리케이션이나 다양한 IoT 기기들이 등장하고 있다. 다양한 IoT 기기나 어플리케이션은 엄청난 양의 트래픽을 발생시킨다. 엄청난 양의 트래픽은 전송속도를 저하시킬 뿐만 아니라, 높은 Quality of Service(QoS)를 보장하기가 힘들다. 또한 이러한 문제점들을 보안하기 위해 Software Defined Networking(SDN)이라는 기술이 빠른속도로 발전하고 있으며, 본 논문에서는 다양한 어플리케이션과 IoT 기기의 트래픽을 SDN환경에서 분류 하며, 트래픽의 분류 정확도와 더 빠른 분류를 위해 트래픽의 특징 선택 기법을 제안한다. 특징 선택을 수행한 뒤, 트래픽 분류를 진행하면 트래픽 분류 정확도를 높이고, 트래픽 분류시간은 줄어드는 효과를 보이며, 높은 QoS를 보장함으로써, 기존 네트워크 트래픽의 부하가 줄어드는 우수한 성능을 보인다.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.1-8
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• 2021

With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2870-2888
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• 2017

Recent studies have shown that the flow table size of hardware SDN switch cannot match the number of concurrent flows. Combined SDN Forwarding Element (CFE), which comprises several software switches and a hardware switch, becomes an alternative approach to tackle this problem. Due to the limited capacity of software switch, the way to route concurrent flows in CFE can largely affect the maximum delay that a flow suffers at CFE. As delay-guarantee is a nontrivial task for network providers with the increasing number of delay-sensitive applications, we propose an analytical model of CFE to evaluate a rules placement solution first. Next, we formulate the problem of Rules Placement with delay guarantee in CFE (RPCFE), and present the genetic-based rules placement (GARP) algorithm to solve the RPCFE problem. Further, we validate the analytical model of CFE through simulations in NS-3 and compare the performance of GARP with three benchmark algorithms.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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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.