• Journal of Communications and Networks
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• 제6권1호
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• pp.46-59
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• 2004

In this paper, we present two algorithms for efficiently aggregating link state information needed for quality-of-service (QoS) routing. In these algorithms, each edge node in a group is mapped onto a node of a shufflenet or a node of a de Bruijn graph. By this mapping, the number of links for which state information is maintained becomes aN (a is an integer, N is the number of edge nodes) which is significantly smaller than N2 in the full-mesh approach. Our algorithms also can support asymmetric link state parameters which are common in practice, while many previous algorithms such as the spanning tree approach can be applied only to networks with symmetric link state parameters. Experimental results show that the performance of our shufflenet algorithm is close to that of the full-mesh approach in terms of the accuracy of bandwidth and delay information, with only a much smaller amount of information. On the other hand, although it is not as good as the shufflenet approach, the de Bruijn algorithm also performs far better than the star approach which is one of the most widely accepted schemes. The de Bruijn algorithm needs smaller computational complexity than most previous algorithms for asymmetric networks, including the shufflenet algorithm.

• Journal of Information Processing Systems
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• 제11권3호
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• pp.465-482
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• 2015

IEEE 802.11p is a standard MAC protocol for wireless access in vehicular environments (WAVEs). If a packet collision happens when a safety message is sent out, IEEE 802.11p chooses a random back-off counter value in a fixed-size contention window. However, depending on the random choice of back-off counter value, it is still possible that less important messages are sent out first while more important messages are delayed longer until sent out. In this paper, we present a new scheme for safety message scheduling, called the enhanced message priority mechanism (EMPM). It consists of the following two components: the benefit-value algorithm, which calculates the priority of the messages depending on the speed, deceleration, and message lifetime; and the back-off counter selection algorithm, which chooses the non-uniform back-off counter value in order to reduce the collision probability and to enhance the throughput of the highly beneficial messages. Numerical results show that the EMPM can significantly improve the throughput and delay of messages with high benefits when compared with existing MAC protocols. Consequently, the EMPM can provide better QoS support for the more important and urgent messages.

• 인터넷정보학회논문지
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• 제4권5호
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• pp.61-68
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• 2003

본 논문에서는 PRMA의 구조를 사용하여 ABR 형태의 데이터 서비스를 수행할 수 있는 알고리즘을 도입하므로서 그 개념을 확장하고, 채널의 이용효율을 극대화하도록 설계된 무선 MAC 알고리즘인 APRMA를 제안한다. 기존의 PRMA에서는 랜덤 데이터를 전송하고자 하는 단말들은 슬롯을 예약한 수 없다. 즉, 슬롯의 예약은 시간 지연에 엄격한 음성에만 국한된다. 그러나 데이터들도 요구하는 서비스 품질을 만족시켜주어야 하며, 이를 위해 데이터에 대해서도 예약을 가능하게 하므로서 채널의 처리율도 높일 수 있다. 따라서, APRMA에서는 초기에는 최소한의 대역만을 할당해주며, 잉여의 대역이 존재하면 계속 그 전송율을 높여나갈 수 있게 하므로서 채널의 이용율을 높이고, 음성과 같은 상대적으로 우선순위가 높은 서비스 요청에 대해서도 동시에 그 서비스 품질을 만족시킬 수 있다.

• 인터넷정보학회논문지
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• 제22권5호
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.327-333
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• 2022

Internet Protocol Television (IPTV) has emerged as a personal entertainment source for home users. Streaming IPTV content over a wireless medium with good Quality of Service (QoS) can be a challenging task as IPTV content requires more bandwidth and Wireless Local Area Networks (WLANs) are susceptible to packet loss, delay and jitter. This research presents the capacity of IPTV using User Datagram Protocol (UDP) and TCP Friendly Rate Control (TFRC) over IEEE 802.11ac WLANs in good and bad network conditions. Experimental results show that in good network conditions, UDP and TFRC could accommodate a maximum of 78 and 75 Standard Definition Television (SDTV) users, respectively. In contrast, 15 and 11 High-Definition Television (HDTV) users were supported by UDP and TFRC, respectively. Performance of UDP and TFRC was identical in bad network conditions and same number of SDTV and HDTV users were supported by TFRC and UDP. With background Transmission Control Protocol (TCP) traffic, both UDP and TFRC can support nearly the same number of SDTV users. It was found that TFRC can co-exist fairly with TCP by giving more throughput to TCP unlike UDP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.874-890
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• 2021

With the widespread deployment of the fifth-generation (5G) communication networks, various real-time applications are rapidly increasing and generating massive traffic on backhaul network environments. In this scenario, network congestion will occur when the communication and computation resources exceed the maximum available capacity, which severely degrades the network performance. To alleviate this problem, this paper proposed an intelligent resource allocation (IRA) to integrate with the extant resource adjustment (ERA) approach mainly based on the convergence of support vector machine (SVM) algorithm, software-defined networking (SDN), and mobile edge computing (MEC) paradigms. The proposed scheme acquires predictable schedules to adapt the downlink (DL) transmission towards off-peak hour intervals as a predominant priority. Accordingly, the peak hour bandwidth resources for serving real-time uplink (UL) transmission enlarge its capacity for a variety of mission-critical applications. Furthermore, to advance and boost gateway computation resources, MEC servers are implemented and integrated with the proposed scheme in this study. In the conclusive simulation results, the performance evaluation analyzes and compares the proposed scheme with the conventional approach over a variety of QoS metrics including network delay, jitter, packet drop ratio, packet delivery ratio, and throughput.

• 인터넷정보학회논문지
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• 제23권2호
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• pp.1-7
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• 2022

Machine learning (ML) algorithms have been intended to seamlessly collaborate for enabling intelligent networking in terms of massive service differentiation, prediction, and provides high-accuracy recommendation systems. Mobile edge computing (MEC) servers are located close to the edge networks to overcome the responsibility for massive requests from user devices and perform local service offloading. Moreover, there are required lightweight methods for handling real-time Internet of Things (IoT) communication perspectives, especially for ultra-reliable low-latency communication (URLLC) and optimal resource utilization. To overcome the abovementioned issues, this paper proposed an intelligent scheme for traffic steering based on the integration of MEC and lightweight ML, namely support vector machine (SVM) for effectively routing for lightweight and resource constraint networks. The scheme provides dynamic resource handling for the real-time IoT user systems based on the awareness of obvious network statues. The system evaluations were conducted by utillizing computer software simulations, and the proposed approach is remarkably outperformed the conventional schemes in terms of significant QoS metrics, including communication latency, reliability, and communication throughput.

• 전기전자학회논문지
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• 제27권4호
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• pp.617-623
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• 2023

통신 망의 진화에 따라 대용량 데이터 기반의 안정적인 고속 데이터 연결이 필요한 서비스들이 증가하고 있다. 사용자의 단말로부터 취합된 패킷 데이터의 용량이 증가하면서 코어 네트워크로 전달하는 중간 링크인 백홀 네트워크의 지연에 대한 품질진단의 중요성이 대두되었다. 본 논문에서는 응용서비스 품질에 영향을 미치는 RTT(Round Trip Time) 지연과 성능저하의 원인이 될 수 있는 회선 대역폭(Bandwidth) 및 스위치 내 속도 불일치, 구간별 버퍼(Buffer) 사이즈, 라우팅 정책 등 여러 인자의 진단을 통하여 백홀 네트워크에서 문제를 해결할 수 있는 기법에 관해 실제 사례를 통해 연구를 진행하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2118-2135
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• 2012

With the rapid development of heterogeneous emerging wireless technologies and numerous types of mobile devices, the need to support robust mobile video streaming based on the seamless handover in Future Internet is growing. To support the seamless handover, several IP-based mobility management protocols such as Mobile IPv6 (MIPv6), fast handover for the MIPv6 (FMIPv6), Hierarchical MIPv6 (HMIPv6) and Proxy Mobile IPv6 (PMIPv6) were developed. However, MIPv6 depreciates the Quality-of-Service (QoS) and FMIPv6 is not robust for the video services in heterogeneous emerging wireless networks when the Mobile Node (MN) may move to another visited network in contrast with its anticipation. In Future Internet, the possibility of mobile video service failure is more increased because mobile users consisting of multiple wireless network interfaces (WNICs) can frequently change the access networks according to their mobility in heterogeneous wireless access networks such as 3Generation (3G), Wireless Fidelity (Wi-Fi), Worldwide Interoperability for Microwave Access (WiMax) and Bluetooth co-existed. And in this environment, seamless mobility is coupled according to user preferences, enabling mobile users to be "Always Best Connected" (ABC) so that Quality of Experience is optimised and maintained. Even though HMIPv6 and PMIPv6 are proposed for the location management, handover latency enhancement, they still have limit of local mobility region. In this paper, we propose a robust mobile video streaming in Heterogeneous Emerging Wireless Systems. In the proposed scheme, the MN selects the best-according to an appropriate metric-wireless technology for a robust video streaming service among all wireless technologies by reducing the handover latency and initiation time when handover may fail. Through performance evaluation, we show that our scheme provides more robust mechanism than other schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권5호
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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.