• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.135-138
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• 2004

This paper considers a ring loading problem on RPR(Resilient Packet Ring), where RPR is recommended by IEEE802.17 Resilient Packet Ring working group for data optimized networks without the requirements of provisioning circuits. RPR is well suitable for metropolitan area network with two counter-rotating rings that multiple stations share the bandwidth, where the data and its corresponding control traffic is transmitted to the two opposite directional ring, respectively. One of the major concerns on RPR is to provide fairness among traffic requirements. The paper discusses several fairness measures and analysis ring loading problems for the fairness.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.143-146
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• 2015

Software Defined Network (SDN) separates control plane and data plane to achieve benefits such as centralized management, centralized provisioning, lower device cost and more flexibility. In SDN, scalability is an important issue. Centralized controller can be a bottle neck and many research tried to solve this issue on the control plan. However, scalability issue does not only happen in the control plane, but also happen in the data plane. In the data plane, flow table is an important component and its size is limited. In a large network operated by SDN technology, the performance of the network can be highly degraded because of the size limitation of a flow table. In this paper, we propose a ranking-based flow replacement method, Flow Table Management (FTM), to overcome this problem.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.634-642
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• 2008

Radio wave is the valuable resources in $21^{st}$ century. It will be widely used in various applications such as DMB, USN, telematics, and home network as well as mobile and wireless communications. Cognitive Radio technology is devised to maximize the utilization of radio resources by sensing near-by spectrum and dynamic and allocating free resources dynamically and adaptively. Wireless links for the secondary user need to be frequently switched to idle frequencies during the transmission of multimedia data in the cognitive radio based system. This may cause delay and information loss, and QoS degradations occur inevitably. The efficient frequency allocation scheme is necessary to support the seamless multimedia service to the secondary user while maintaining QoS of the primary user. This paper suggests a frequency selection scheme which considers other parameters such as cell load, data rate, and available bandwidth than just received signal strength during the frequency selection process. The performance of our proposed scheme is analyzed by simulation.

• Asia pacific journal of information systems
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• v.30 no.1
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• pp.94-119
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• 2020

Digital platforms characterized by network effects enable provisioning of various types of services and provide a mechanism for linking producers and consumers. Identifying the key Quality of Service attributes of such platforms is vital for their continued success and growth. In this paper, a set of quality attributes for platforms is first extracted from different extant quality models. Then actual user feedback data from three platform providers are analysed and mapped against the set of quality attributes to determine the key attributes that are relevant. These findings are corroborated with qualitative data from interviews of different stakeholders. The results show that service quality characteristics are important to the success of platforms. Functional characteristics of platforms assume importance where the digital contributions of the platform is higher. Apart from these, 'fitness for use' as a major determinant of quality is also important in digital platforms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.720-740
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• 2011

Wi-Fi-enabled portable devices have recently been introduced into the consumer electronics market. These devices download or upload content, from or to a host machine, such as a personal computer, a laptop, a home gateway, or a media server. This paper investigates the fairness among multiple Wi-Fi-enabled portable devices in a home network when they are simultaneously communicated with the host machine. First, we present that, a simple IEEE 802.11-based home network suffers from unfairness, and the fairness is exaggerated by the wireless link errors. This unfairness is due to the asymmetric response of the TCP to data-packet loss and to acknowledgment-packet loss, and the wireless link errors that occur in the proximity of any node; the errors affect other wireless devices through the interaction at the interface queue of the home gateway. We propose a QoS-provisioning framework in order to achieve per-device fairness and service differentiation. For this purpose, we introduce the medium access price, which denotes an aggregate value of network-wide traffic load, per-device link usage, and per-device link error rate. We implemented the proposed framework in the ns-2 simulator, and carried out a simulation study to evaluate its performance with respect to fairness, service differentiation, loss and delay. The simulation results indicate that the proposed method enforces the per-device fairness, regardless of the number of devices present and regardless of the level of wireless link errors; furthermore it achieves high link utilization with only a small amount of frame losses.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.4
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• pp.497-507
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• 2018

Tactical networks are evolving into an All-IP based network for network centric warfare(NCW). Owing to the flexibility of IP based network, various military data applications including real-time and multi-media services are being integrated in tactical networks. Because each application has diverse Quality-of-service(QoS) requirements, it is crucial to develop a QoS provisioning method for guaranteeing QoS requirements efficiently. Conventionally, differentiated services(DiffServ) have been used to provide a different level of QoS for traffic flows. However, DiffServ is not designed to guarantee a specific requirement of QoS such as delay, loss, and bandwidth. Therefore, it is not suitable for military applications with a tight bound of QoS requirements. In this paper, we propose a multi-layer network virtualization scheme that allocates traffic flows having different QoS requirements to multiple virtual networks, which are constructed to support different QoS policies such as virtual network functions(VNFs), routing, queueing/active queue management(AQM), and physical layer policy. The experiment results indicate that the proposed scheme achieves lower delays and losses through multiple virtual networks having differentiated QoS policies in comparison with conventional networks.

• Journal of Service Research and Studies
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• v.2 no.2
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• pp.91-98
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• 2012

The emergence of new types of embedded computing devices and developments in wireless networking are broadening the domain of computing from the work place and home office to other facets of everyday life. This trend is expected to lead to a proliferation of Internet of Things (IoT) environments, in which inexpensive and interconnected computing devices are capable of supporting users in a range of tasks. Context-aware computing is a key source to develop such smart services. However, there are many challenges to enable services to be smart; Heterogeneous Computing Environments, Resource Limitations, Large Amount of Data Produced, and Different Requirements for Context Interpretation. Because of these challenges, there are difficulties in providing smart service by utilizing IoT devices. Currently, many researchers are conducting researches on mobile-computing based smart service development and provisioning and network infrastructure for interconnected IoT devices. Still, there are some limitations on developing core technologies for IoT computing based smart service development. In order to remedy this situation, this thesis presents a reusable framework that provides unique and noble features which are required in developing advanced context-aware IoT applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5723-5743
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• 2018

The evolving internet-based services demand high-speed data transmission in conjunction with scalability. The next generation optical network has to exploit artificial intelligence and cognitive techniques to cope with the emerging requirements. This work proposes a novel way to solve the dynamic provisioning problem in optical network. The provisioning in optical network involves the computation of routes and the reservation of wavelenghs (Routing and Wavelength assignment-RWA). This is an extensively studied multi-objective optimization problem and its complexity is known to be NP-Complete. As the exact algorithms incurs more running time, the heuristic based approaches have been widely preferred to solve this problem. Recently the software-defined networking has impacted the way the optical pipes are configured and monitored. This work proposes the dynamic selection of path computation algorithms in response to the changing service requirements and network scenarios. A software-defined controller mechanism with a novel packet matching feature was proposed to dynamically match the traffic demands with the appropriate algorithm. A software-defined controller with Path Computation Element-PCE was created in the ONOS tool. A simulation study was performed with the case study of dynamic path establishment in ONOS-Open Network Operating System based software defined controller environment. A java based NOX controller was configured with a parent path computation element. The child path computation elements were configured with different path computation algorithms under the control of the parent path computation element. The use case of dynamic bulk path creation was considered. The algorithm selection method is compared with the existing single algorithm based method and the results are analyzed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.436-438
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• 2015

In this paper, a P2P Standard Group Formation (P2P-SGF) method in Wi-Fi Direct is presented to provide direct communication services between Internet-of-Things (IoT) gateways. Generally, network traffic congestion and speed reduction problems are caused when transmitting mass data as well as measured data from many sensors between IoT gateways via an Access Point (AP). For solving these problems, it is required to implement Wi-Fi Direct efficiently transmitting mass data between IoT gateways without passing through the AP. The implemented P2P-SGF method basically performs Discovery, GO (Group Owner) Negotiation, WPS (Wi-Fi Protected Setup) Provisioning, and Address Configuration. Especially, it supports the DLNA (Digital Living Network Alliance) service function for sharing mass data between IoT gateways. Some experimental results verify that it can successfully share large video files.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.55-60
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• 2020

Adaptive recommendation systems have been developed with big data processing as a system that provides services tailored to users based on user information and usage patterns. Deep learning can be used in these adaptive recommendation systems to handle big data, providing more efficient user-friendly recommendation services. In this paper, we propose a system that uses deep learning to categorize and recommend tourism types to suit the user's personality. The system was divided into three layers according to its core role to increase efficiency and facilitate maintenance. Each layer consists of the Service Provisioning Layer that real users encounter, the Recommendation Service Layer, which provides recommended services based on user information entered, and the Adaptive Definition Layer, which learns the types of tourism suitable for personality types. The proposed system is highly scalable because it provides services using deep learning, and the adaptive recommendation system connects the user's personality type and tourism type to deliver the data to the user in a flexible manner.