• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.859-876
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• 2010

In this paper, we propose a hierarchical application traffic classification system as an alternative means to overcome the limitations of the port number and payload based methodologies, which are traditionally considered traffic classification methods. The proposed system is a new classification model that hierarchically combines a binary classifier SVM and Support Vector Data Descriptions (SVDDs). The proposed system selects an optimal attribute subset from the bi-directional traffic flows generated by our traffic analysis system (KU-MON) that enables real-time collection and analysis of campus traffic. The system is composed of three layers: The first layer is a binary classifier SVM that performs rapid classification between P2P and non-P2P traffic. The second layer classifies P2P traffic into file-sharing, messenger and TV, based on three SVDDs. The third layer performs specialized classification of all individual application traffic types. Since the proposed system enables both coarse- and fine-grained classification, it can guarantee efficient resource management, such as a stable network environment, seamless bandwidth guarantee and appropriate QoS. Moreover, even when a new application emerges, it can be easily adapted for incremental updating and scaling. Only additional training for the new part of the application traffic is needed instead of retraining the entire system. The performance of the proposed system is validated via experiments which confirm that its recall and precision measures are satisfactory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1479-1495
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• 2012

Spectrum scarcity seems to be the most challenging issue to be solved in new wireless telecommunication services. It is shown that spectrum unavailability is mainly due to spectrum inefficient utilization and inappropriate physical layer execution rather than spectrum shortage. Daily increasing demand for new wireless services with higher data rate and QoS level makes the upgrade of the physical layer modulation techniques inevitable. Orthogonal Frequency Division Multiple Access (OFDMA) which utilizes multicarrier modulation to provide higher data rates with the capability of flexible resource allocation, although has widely been used in current wireless systems and standards, seems not to be the best candidate for cognitive radio systems. Filter Bank based Multi-Carrier (FBMC) is an evolutionary scheme with some advantages over the widely-used OFDM multicarrier technique. In this paper, we focus on the total throughput improvement of a cognitive radio network using FBMC modulation. Along with this modulation scheme, we propose a novel uplink radio resource allocation algorithm in which fairness issue is also considered. Moreover, the average throughput of the proposed FBMC based cognitive radio is compared to a conventional OFDM system in order to illustrate the efficiency of using FBMC in future cognitive radio systems. Simulation results show that in comparison with the state of the art two algorithms (namely, Shaat and Wang) our proposed algorithm achieves higher throughputs and a better fairness for cognitive radio applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1481-1500
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• 2016

Device-to-Device (D2D) communication underlaying macro-small cell networks, as one of the promising technologies in the era of 5G, is able to improve spectral efficiency and increase system capacity. In this paper, we model the cross- and co-tier D2D communications in two-tier macro-small cell networks. To avoid the complicated interference for cross-tier D2D, we propose a mode selection scheme with a dedicated resource sharing strategy. For co-tier D2D, we formulate a joint optimization problem of power control and resource reuse with the aim of maximizing the overall outage capacity. To solve this non-convex optimization problem, we devise a heuristic algorithm to obtain a suboptimal solution and reduce the computational complexity. System-level simulations demonstrate the effectiveness of the proposed method, which can provide enhanced system performance and guarantee the quality-of-service (QoS) of all devices in two-tier macro-small cell networks. In addition, our study reveals the high potential of introducing cross- and co-tier D2D in small cell networks: i) cross-tier D2D obtains better performance at low and medium small cell densities than co-tier D2D, and ii) co-tier D2D achieves a steady performance improvement with the increase of small cell density.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.27-34
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• 2010

As VoIP systems move to wireless environments with much higher average packet loss rates than wired networks, it becomes less possible for the network to assure a reasonable QoS. So, real-time quality monitoring for mobile VoIP applications is an important issue to be explored. In this paper, we explore perceptual quality dependency on two parameters: the burst loss rate and average burst length. Also, we propose a simple 'moving average' approach with $\alpha$ aiming to measure those parameters on real-time basis. In order to find how accurately the two parameters measured estimate the real perceptual quality, we compare actual measured PESQ scores with estimated value by matching the measured quality metric to the trained MOS table. Finally, we propose the quality-based accounting system, which can set obvious continuities between quality and billing.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.3
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• pp.269-274
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• 2010

Recently IPTV service is becoming an emerging service representing IP convergence that is enabled on the broadband networks. It is an essential and very important issue to manage the service quality of IPTV service effectively for its successful deployment because of the innate nature of current Internet that cannot support quality of service (QoS). In particular, it is required that subscriber can measure and judge the service quality of IPTV service directly, which is impossible with the current method usually depending on a measurement equipment. In this paper, therefore, we introduce an implementation of a software that is installed at a set-top on the subscriber side and measures the quality of IPTV service in real time. In order to verify the performance of the implemented software, we perform a number of tests and compare the result with the measurement equipments in common use. By the comparison, it is shown that the measurement by the implemented software is precise and reliable.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.978-980
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• 2006

A Next Generation Network (NGN) is a packet-based network able to provide services including Telecommunication Services and able to make use of multiple broadband, QoS-enabled transport technologies and in which service-related functions are independent from underlying transport-related technologies. It offers unrestricted access by users to different service providers. It supports generalized mobility which will allow consistent and ubiquitous provision of services to users In this paper, we explain the trend of standardization activity related with open services in ITU-T SG13(Study Group 13). ITU-T SG13 is responsible for studies .elating to the architecture, evolution and convergence of next generation networks including frameworks and functional architectures, signalling requirements for NGN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.91-107
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• 2014

Device-to-device (D2D) communication is an excellent technology to improve the system capacity by sharing the spectrum resources of cellular networks. Multicast service is considered as an effective transmission mode for the future mobile social contact services. Therefore, multicast based on D2D technology can exactly improve the spectrum resource efficiency. How to apply D2D technology to support multicast service is a new issue. In this paper, a resource allocation scheme based on cognitive radio (CR) for D2D underlay multicast communication (CR-DUM) is proposed to improve system performance. In the cognitive cellular system, the D2D users as secondary users employing multicast service form a group and reuse the cellular resources to accomplish a multicast transmission. The proposed scheme includes two steps. First, a channel allocation rule aiming to reduce the interference from cellular networks to receivers in D2D multicast group is proposed. Next, to maximize the total system throughput under the condition of interference and noise impairment, we formulate an optimal transmission power allocation jointly for the cellular and D2D multicast communications. Based on the channel allocation, optimal power solution is in a closed form and achieved by searching from a finite set and the interference between cellular and D2D multicast communication is coordinated. The simulation results show that the proposed method can not only ensure the quality of services (QoS), but also improve the system throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1492-1512
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• 2011

Due to multiple hops, mobility and time-varying channel, supporting delay sensitive real-time traffic in wireless local area network-based (WLAN) mesh networks is a challenging task. In particular for real-time traffic subject to medium access control (MAC) layer control overhead, such as preamble, carrier sense waiting time and the random backoff period, the performance of real-time flows will be degraded greatly. In order to support real-time traffic, an efficient adaptive packet scheduling (APS) scheme is proposed, which aims to improve the system performance by guaranteeing inter-class, intra-class service differentiation and adaptively adjusting the packet length. APS classifies incoming packets by the IEEE 802.11e access class and then queued into a suitable buffer queue. APS employs strict priority service discipline for resource allocation among different service classes to achieve inter-class fairness. By estimating the received signal to interference plus noise ratio (SINR) per bit and current link condition, APS is able to calculate the optimized packet length with bi-dimensional markov MAC model to improve system performance. To achieve the fairness of intra-class, APS also takes maximum tolerable packet delay, transmission requests, and average allocation transmission into consideration to allocate transmission opportunity to the corresponding traffic. Detailed simulation results and comparison with IEEE 802.11e enhanced distributed channel access (EDCA) scheme show that the proposed APS scheme is able to effectively provide inter-class and intra-class differentiate services and improve QoS for real-time traffic in terms of throughput, end-to-end delay, packet loss rate and fairness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3B
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• pp.274-287
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• 2009

In the Internet environment in which best-effort services are provided, we need to guarantee end-to-end performance rather than hop performance to provide services with a variety of QoS(Quality of Service) requirements. The end-to-end performance is affected by many factors along the path of traffic flow. Most existing simulation studies are concentrated on a single node or a few nodes. We need much different approach considering the simulation execution time to simulate a large-scale network. In this paper, we derive requirements and present methodologies for the implementation of the simulator to simulate it. Then, we design and implement our simulator using OPNET. Performance evaluation is carried out using the simulator for large-scale KII (National Information Infrastructure in Korea). We use a self-similar traffic model and present some results on the end-to-end performance metric for the networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.