• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.47-48
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• 2019

본 논문에서는 신경망의 일종인 자기조직화지도(Self Organizing Map)을 이용하여 컨트롤러의 순서를 정하는 모델을 제안하였다. 자기조직화지도는 자율 학습에 의한 클러스터링을 수행하는 알고리즘으로써 컨트롤러에 가중치를 부여하고 컨트롤러 간 거리를 계산하여 효율적인 컨트롤러 선택을 목표로 한다.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.187-193
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• 2023

Large software systems are being produced with a noticeably higher level of quality with component-based software engineering (CBSE), which places a strong emphasis on breaking down engineered systems into logical or functional components with clearly defined interfaces for inter-component communication. The component-based software engineering is applicable for the commercial products of open-source software. Software metrics play a major role in application development which improves the quantitative measurement of analyzing, scheduling, and reiterating the software module. This methodology will provide an improved result in the process, of better quality and higher usage of software development. The major concern is about the software complexity which is focused on the development and deployment of software. Software metrics will provide an accurate result of software quality, risk, reliability, functionality, and reusability of the component. The proposed metrics are used to assess many aspects of the process, including efficiency, reusability, product interaction, and process complexity. The details description of the various software quality metrics that may be found in the literature on software engineering. In this study, it is explored the advantages and disadvantages of the various software metrics. The topic of component-based software engineering is discussed in this paper along with metrics for software quality, object-oriented metrics, and improved performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.34-41
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• 2017

Wireless mesh networks contain multi-hop routing protocols between wireless nodes and are connected to the Internet through a gateway. These networks perform a role as a backbone and are scalable for main applications. We propose the design of QoS supporting mechanisms for wireless mesh networks using software defined networking. Our proposed scheme is cost-effective and features adaptive QoS mechanisms for wireless router's resource constraints. The QoS mechanisms use software defined networking technology with Openflow protocol based on diffserv and intserv models with MPLS mechanism and RSVP respectively. A performance evaluation model is suggested to verify the validity of the proposed scheme using several QoSmetrics of the wireless mesh networks.

• Journal of KIISE
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• v.44 no.9
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• pp.976-985
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• 2017

Wireless mesh network (WMN) is a promising technology for building a cost-effective and easily-deployed wireless networking infrastructure. To efficiently utilize limited radio resources in WMNs, packet transmissions (particularly, redundant packet transmissions) should be carefully managed. We therefore propose a lightweight traffic redundancy elimination (LTRE) scheme to reduce redundant packet transmissions in software-defined wireless mesh networks (SD-WMNs). In LTRE, the controller determines the optimal path of each packet to maximize the amount of traffic reduction. In addition, LTRE employs three novel techniques: 1) machine learning (ML)-based information request, 2) ID-based source routing, and 3) popularity-aware cache update. Simulation results show that LTRE can significantly reduce the traffic overhead by 18.34% to 48.89%.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.4
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• pp.80-88
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• 2019

Software Defined Networking (SDN) is the future network paradigm of decoupling control and data functions. In SDN structure, it is hard to address scalability in case of large-scale networks because single controller managed thousands of switches in a centralized fashion. Most of previous studies have focused on horizontal scalability, where distributed controllers are assigned to network devices. However, they have abstracted the control plane and the application plane into a single controller. The layer of the common SDN architecture is divided into data plane, control plane, and application plane, but the control plane and application plane have been modeled as a single controller although they are logically separated. In this paper, we propose a analytical traffic model considering the both application plane and control plane based on queuing theory. This model can be used to address scalability issues such as controller placement problem without complicated simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4A
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• pp.335-341
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• 2008

The SDR(Software Defined Radio) system for hardware and software must be an open structure to various system standards. It should also provide a capability of distributed processing, object-orientedness, and software controllability. It implies that the software to be used in the SDR system should provide the openness such that it can operate independently of a given hardware platform. In order to achieve these goals, the SDR system tends to modularization for increasing hardware reuse and design flexibility, which provides the system reconfigurability. In this paper, we implemented a base station with proposed an open architecture of a Smart Antenna Base Station(SABS) and Smart Antenna APIs[10] operating in SDR network in such a way that the architecture itself is suitable for the entire system to maintain the openness, object-orientedness, and software controllability.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.144-155
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• 2019

One of the issues of the automotive industry today is autonomous driving vehicles. In order to achieve level 3 or higher as defined by SAE International, harmonization of autonomous driving technology and connected technology is essential. Current vehicles have new features such as autonomous driving, which not only increases the number of electrical components, but also the amount and complexity of software. As a result, the attack surface, which is the access point of attack, is widening, and software security vulnerabilities are also increasing. However, the reality is that the essential security requirements for vehicles are not defined. In this paper, based on real attacks and vulnerability cases and trends, we identify the assets in the in-vehicle network and derive the threats. We also defined the security requirements and derived essential security requirements that should be applied at least to the safety of the vehicle occupant through risk analysis.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1153-1160
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• 2021

This paper proposes a routing algorithm that determines the optimal path using deep reinforcement learning in software-defined networks. The deep reinforcement learning model for learning is based on DQN, the inputs are the current network state, source, and destination nodes, and the output returns a list of routes from source to destination. The routing task is defined as a discrete control problem, and the quality of service parameters for routing consider delay, bandwidth, and loss rate. The routing agent classifies the appropriate service class according to the user's quality of service profile, and converts the service class that can be provided for each link from the current network state collected from the SDN. Based on this converted information, it learns to select a route that satisfies the required service level from the source to the destination. The simulation results indicated that if the proposed algorithm proceeds with a certain episode, the correct path is selected and the learning is successfully performed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.79-95
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• 2016

In order to improve the Quality-of-Service (QoS) of latency sensitive applications in next-generation cellular networks, multi-path is adopted to transmit packet stream in real-time to achieve high-quality video transmission in heterogeneous wireless networks. However, multi-path also introduces two important challenges: out-of-order issue and reordering delay. In this paper, we propose a new architecture based on Software Defined Network (SDN) for flow aggregation and flow splitting, and then design a Multiple Access Radio Scheduling (MARS) scheme based on relative Round-Trip Time (RTT) measurement. The QoS metrics including end-to-end delay, throughput and the packet out-of-order problem at the receiver have been investigated using the extensive simulation experiments. The performance results show that this SDN architecture coupled with the proposed MARS scheme can reduce the end-to-end delay and the reordering delay time caused by packet out-of-order as well as achieve a better throughput than the existing SMOS and Round-Robin algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2735-2751
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• 2020

The emergence of Software Defined Networking (SDN) overcomes the limitations of traditional networking architectures. There are some advantages in SDN which are centralized global network view, programmability, and separation of the data plane and control plane. Due to the limitation of data plane storage capacity in SDN, it is necessary to process the redundancy rules of switch. In this paper, we propose a method for active detection and processing of redundant rules. We use the result generated by the customized probe package to detect redundant rules. And by checking the forwarding behavior of probe packets in the data plane, the redundancy rules are further processed. Furthermore, in order to quickly check the dynamic networks, we propose an incremental algorithms for rapidly evolve the network strategies. We conduct simulation experiments on Matlab to verify the feasibility of the algorithm. The influence of some parameters on the result are discussed.