• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.121.1-121
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• 2001

Congestion control is a critical issue in TCP networks, Recently, active queue management (AQM) was proposed for congestion control at routers. The random early detection RED algorithm is widely known in the AQM algorithms, We present an adaptive nonlinear RED (NRED) algorithm, which has nonlinear drop probability profile. The proposed algorithm enhanced the performance of the RED algorithm by the self-parameterization based on the traffic load Furthermore, the proposed algorithm can effectively adapt itself between he RED and the drop-tail queue management by adopting proper nonlinearity in the drop probability profile. Through simulation, we show the effectiveness of the proposed algorithm comparing with the drop-tail and the original RED algorithm.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.461-467
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• 2014

Active queue management (AQM) algorithms run on routers and detect incipient congestion by typically monitoring the instantaneous or average queue size. When the average queue size exceeds a certain threshold, AQM algorithms infer congestion on the link and notify the end systems to back off by proactively dropping some of the packets arriving at a router or marking the packets to reduce transmission rate at the sender. Among the existing AQM algorithms, random early detection (RED) is well known as the representative queue-based management scheme by randomizing packet dropping. To reduce the number of timeouts in TCP and queuing delay, maintain high link utilization, and remove bursty traffic biases, the RED considers an average queue size as a degree of congestions. However, RED do not well in the specified networks conditions due to the fixed parameters($P_{max}$ and $TH_{min}$) of RED. This paper addresses a extended RED to be adapted in various networks conditions. By sensing network state, $P_{max}$ and $TH_{min}$ can be automatically changed to proper value and then RED do well in various networks conditions.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.1-13
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• 2010

It is not easy to set RED(Random Early Detection) parameter according to environment in managing Network Device. Especially, it is more difficult to set parameter in the case of maintaining the constant service rate according to the change of environment. In this paper, we hypothesize the router that has Multi-core CPU in output queue and propose AI RED(Artificial Intelligence RED), which directly induces Genetic Algorithm of Artificial Intelligence in the output queue that is appropriate to the optimization of parameter according to RED environment, which is automatically adaptive to workload. As a result, AI RED Is simpler and finer than FuRED(Fuzzy-Logic-based RED), and RED parameter that AI RED searches through simulations is more adaptive to environment than standard RED parameter, providing the effective service. Consequently, the automation of management of RED parameter can provide a manager with the enhancement of efficiency in Network management.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.372-375
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• 2008

IEEE 802.11e standardized the EDCA mechanism to support the priority based QoS. And the virtual collision handler schedules the transmission time of each MAC frame using the internal back-off window according to the access category(AC). This can provides the differentiated QoS to real-time services at the medium traffic load condition. However, the transmission delay of MAC frame for real-time services may be increased as the traffic load of best effort service increases. It becomes more critical when the real-time service uses a compressed mode video codec such as moving picture experts group(MPEG) 4 codec. That is because each frame has the different importance. That is, the I-frame has more information as compared with the P- and the B-frame. In this paper, we proposed a buffer management algorithm based on the frame importance and the delay bound. The proposed algorithm is consisted of the traffic regulator based on the dual token bucket algorithm and the active queue management algorithm. The traffic regulator reduces the transmission rate of lower AC until that the virtual collision handler can transmit an I-frame. And the active queue management discards frame based on the importance of each frame and the delay bound of head of line(HoL) frame when the channel resource is insufficient.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.767-771
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• 2004

In this paper the performance of some control theory-based Active Queue Management (AQM) methods are improved and investigated through simulation. The simulation scenario is considered to be closely realistic, in which the traffic is mainly due to http sessions. The results show the best performance of PID controller with respect to the others in good queue regulation as well as high link utilization and low delay metrics.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1807-1808
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• 2006

In this paper, we present the wavelet neural network (WNN) controller as an active queue management(AQM) in end-to-end TCP network. AQM is important to regulate the queue length and short round trip time by passing or dropping the packets at the intermediate routers. As the role of AQM, the WNN controller adaptively controls the dropping probability of the TCP network and is trained by gradient-descent algorithm. We illustrate our result that WNN controller is superior to PI controller via simulations.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.526-533
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• 2008

We propose a wavelet neural network (WNN) control method for active queue management (AQM) in an end-to-end TCP network, which is trained by adaptive learning rates (ALRs). In the TCP network, AQM is important to regulate the queue length by passing or dropping the packets at the intermediate routers. RED, PI, and PID algorithms have been used for AQM. But these algorithms show weaknesses in the detection and control of congestion under dynamically changing network situations. In our method, the WNN controller using ALRs is designed to overcome these problems. It adaptively controls the dropping probability of the packets and is trained by gradient-descent algorithm. We apply Lyapunov theorem to verify the stability of the WNN controller using ALRs. Simulations are carried out to demonstrate the effectiveness of the proposed method.

• ETRI Journal
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• v.30 no.2
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• pp.194-204
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• 2008

The online collection of coarse-grained traffic information, such as the total number of flows, is gaining in importance due to a wide range of applications, such as congestion control and network security. In this paper, we focus on an active queue management scheme called SRED since it estimates the number of active flows and uses the quantity to indicate the level of congestion. However, SRED has several limitations, such as instability in estimating the number of active flows and underestimation of active flows in the presence of non-responsive traffic. We present a Markov model to examine the capability of SRED in estimating the number of flows. We show how the SRED cache hit rate can be used to quantify the number of active flows. We then propose a modified SRED scheme, called hash-based two-level caching (HaTCh), which uses hashing and a two-level caching mechanism to accurately estimate the number of active flows under various workloads. Simulation results indicate that the proposed scheme provides a more accurate estimation of the number of active flows than SRED, stabilizes the estimation with respect to workload fluctuations, and prevents performance degradation by efficiently isolating non-responsive flows.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.782-787
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• 2004

Internet Engineering Task Force (IETF) has been considering the deployment of the Random Early Detection (RED) in order to avoid the increasing of packet loss rates which caused by an exponential increase in network traffic and buffer overflow. Although RED mechanism can prevent buffer overflow and hence reduce an average values of packet loss rates, but this technique is ineffective in preventing the consecutive drop in the high traffic condition. Moreover, it increases a probability and average number of consecutive dropped packet in the low traffic condition (named as "uncritical condition"). RED mechanism effects to TCP congestion control that build up the consecutive of the unnecessary transmission rate reducing; lead to low utilization on the link and consequently degrade the network performance. To overcome these problems, we have proposed a new mechanism, named as Extended Drop slope RED (ExRED) mechanism, by modifying the traditional RED. The numerical and simulation results show that our proposed mechanism reduces a drop probability in the uncritical condition.