• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.417-424
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• 2003

In this paper, we introduce and analyze a feedback control model of TCP/AQM dynamics. Then, we propose the Pro-active Queue Management (PAQM) mechanism, which can provide proactive congestion avoidance and control using an adaptive congestion indicator and a control function for wide range of traffic environments. The PAQM stabilizes the queue length around a desired level while giving smooth and low packet loss rates independent of the traffic load level under a wide range of traffic environment. The PAQM outperforms other AQM algorithms such as Random Early Detection (RED) [1] and PI-controller [2]

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1099-1104
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• 2020

In order to provide various types of application services based on the Internet, it is ideal to guarantee the quality of service(QoS) for each flow. However, realizing these ideas is not an easy task.. It is effective to classify multiple flows having the same or similar service quality requirements into same group, and to provide service quality for each group. The queue management mechanism in the router plays a very important role in order to efficiently transmit data and to support differentiated quality of service for each service. In order to efficiently support various multimedia services, an intelligent and adaptive queue management mechanism is required. This paper proposes an intelligent queue management mechanism based on deep reinforcement learning that decides whether to deliver packets for each group based on the traffic information of each flow group flowing in for a certain period of time and the current network state information.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.80-91
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• 2010

Due to the convergence of broadcasting and communications, IPTV services are spotlighted as the that next-generation multimedia services. IPTV services should have functionality such as unlimited channel capacity, extension of media, QoS awareness and are required increasing traffic and quality control technology to adapt the attributes of IPTV service. Consequently, flow based quality control techniques are needed. Therefore, many studies for providing Internet QoS are performed at IETF (Internet Engineering Task Force). As the buffer management mechanism among IP QoS methods, active queue management method such as RED(Random Early Detection) and modified RED algorithms have proposed. However, these algorithms have difficulties to satisfy the requirements of various Internet user QoS. Therefore, in this paper we propose the Flow based AQM(Active Queue Management) algorithm for the multimedia services that request various QoS requirements. The proposed algorithm can converge the packet loss ratio to the target packet loss ratio of required QoS requirements. And we present a performance evaluation by the simulations using the ns-2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6B
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• pp.605-614
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• 2009

Existing Internet services were almost supported by the best effort service such as the data transmission service and were allowed the transmission delay and packet loss. However, recent Internet multimedia services such as Internet phone, Internet broadcasting are required a real-time processing and high bandwidth. Therefore, many studies for providing Internet QoS are performed at IETF (Internet Engineering Task Force). As the buffer management mechanism among IP QoS methods, active queue management method such as RED (Random Early Detection) algorithm has proposed. However, RED algorithm has a limitation of usage of an average buffer length and unfairness. So, many algorithms proposed as the modified algorithm of RED. But these modified algorithms also have difficulties to satisfy the requirements of various Internet user QoS. Therefore, in this paper we propose the QoS adaptive AQM (Active Queue Management) algorithm for the multimedia services that request various QoS requirements and present a performance evaluation by the simulations using the ns-2.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.337-352
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• 2005

In this paper, a fuzzy logic implementation of the random early detection (RED) mechanism [1] is presented. The main objective of the proposed fuzzy controller is to reduce the loss probability of the RED mechanism without any change in channel utilization. Based on previous studies, it is clear that the performance of RED algorithm is extremely related to the traffic load as well as to its parameters setting. Using fuzzy logic capabilities, we try to dynamically tune the loss probability of the RED gateway. To achieve this goal, a two-input-single-output fuzzy controller is used. To achieve a low packet loss probability, the proposed fuzzy controller is responsible to control the $max_{p}$ parameter of the RED gateway. The inputs of the proposed fuzzy controller are 1) the difference between average queue size and a target point, and 2) the difference between the estimated value of incoming data rate and the target link capacity. To evaluate the performance of the proposed fuzzy mechanism, several trials with file transfer protocol (FTP) and burst traffic were performed. In this study, the ns-2 simulator [2] has been used to generate the experimental data. All simulation results indicate that the proposed fuzzy mechanism out performs remarkably both the traditional RED and Adaptive RED (ARED) mechanisms [3]-[5].

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11A
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• pp.867-875
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• 2003

Current end-to-end congestion control depends only on the information of end points (using three duplicate ACK packets) and generally responds slowly to the network congestion. This mechanism can't avoid TCP global synchronization in which TCP congestion window size is fluctuated during congestion period. Furthermore, if RTT(Round Trip Time) is increased, three duplicate ACK packets are not correct congestion signals because congestion might already disappear and the host may send more packets until it receives three duplicate ACK packets. Recently there are increasing interests in solving end-to-end congestion control using AQM(Active Queue Management) to improve the performance of TCP protocols. AQM is a variation of RED-based congestion control. In this paper, we first evaluate the effectiveness of the current AQM schemes such as RED, CHOKe, ARED, FRED and SRED, over traffic with different rates and over traffic with mixed responsive and non-responsive flows, respectively. In particular, CHOKe mechanism shows greater unfairness, especially when more unresponsive flows exist in a shared link. We then propose a new AQM scheme using CHOKe mechanism, called DQC(Double Queue CHOKe), which uses two FIFO queues before applying CHOKe mechanism to adaptive congestion control. Simulation shows that it works well in protecting congestion-sensitive flows from congestion-causing flows and exhibits better performances than other AQM schemes. Also we use partial state information, proposed in LRURED, to improve our mechanism.

• Journal of KIISE
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• v.44 no.2
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• pp.213-222
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• 2017

The Internet of Things (IoT) technology is rapidly developing in recent years, and is applicable to various fields. A smart factory is one wherein all the components are organically connected to each other via a WSN, using an intelligent operating system and the IoT. A smart factory technology is used for flexible process automation and custom manufacturing, and hence needs adaptive network management for frequent network fluctuations. Moreover, ensuring the timeliness of the data collected through sensor nodes is crucial. In order to ensure network timeliness, the power consumption for information exchange increases. In this paper, we propose an IEEE 802.15.4e DSME-based distributed scheduling algorithm for mobility support, and we evaluate various performance metrics. The proposed algorithm adaptively assigns communication slots by analyzing the network traffic of each node, and improves the network reliability and timeliness. The experimental results indicate that the throughput of the DSME MAC protocol is better than the IEEE 802.15.4e TSCH and the legacy slotted CSMA/CA in large networks with more than 30 nodes. Also, the proposed algorithm improves the throughput by 15%, higher than other MACs including the original DSME. Experimentally, we confirm that the algorithm reduces power consumption by improving the availability of communication slots. The proposed algorithm improves the power consumption by 40%, higher than other MACs.