• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7B
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• pp.481-488
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• 2005

As the demand on the multimedia application increases, the congestion control algorithm for the multimedia applications becomes an important research issue. The ultimate goal of congestion control is to adapt the trans-mission rate at the sender to the mont of network resource available on the forward path. In general, the congestion control algorithms use the round trip time(RTT) to estimate the network congestion on the forward path. however, since the RTT includes the delay on both forward and backward paths, it is possible for the algorithms using the RTT to make a wrong decision such as deciding the congestion on the forward path due to the congestion built on the backward path. In this paper, we enhance the performance of RRC-OTT(Receiver-based rate control with one-way Trip Time) algorithm, which uses the one-way trip time(OTT) to estimate the network congestion. By separating the estimation mechanism on the forward path from the backward path, the performance of RRC-OTT algorithm is hardly affected by the congestion built on the backward path.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.336-343
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• 2002

Nowadays, after appearance of wireless network the existent internet environment is changing into the united wire/wireless network. But the present TCP regards all of the packet losses on transmission as the packet tosses due to the congestion. When it is applied on the wireless path, it deteriorates the end-to-end TCP throughput because it regards the packet loss by handoff or bit error as the packet loss by the congestion and it reduces the congestion window. In this paper, for solving these problems we propose the method that controls the performance of TCP on the wireless link by extending ECN which is used as a congestion control mechanism on the existent wire link. This is the method that distinguished the packet loss due to the congestion from due to bit error or handoff on the wireless network, so it calls the congestion control mechanism only when there occurs the congestion in the united wire/wireless network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Journal of Computing Science and Engineering
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• v.1 no.1
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• pp.31-55
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• 2007

Contemporary end-servers and network-routers rely on traffic shaping to deal with server overload and network congestion. Although such traffic shaping provides a means to mitigate the effects of server overload and network congestion, the lack of cooperation between end-servers and network-routers results in waste of network resources. To remedy this problem, we design, implement, and evaluate NetDraino, a novel mechanism that extends the existing queue-management schemes at routers to exploit the link congestion information at downstream end-servers. Specifically, NetDraino distributes the servers' traffic-shaping rules to the congested routers. The routers can then selectively discard those packets-as early as possible-that overloaded downstream servers will eventually drop, thus saving network resources for forwarding in-transit packets destined for non-overloaded servers. The functionality necessary for servers to distribute these filtering rules to routers is implemented within the Linux iptables and iproute2 architectures. Both of our simulation and experimentation results show that NetDraino significantly improves the overall network throughput with minimal overhead.

• Proceedings of the IEEK Conference
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• summer
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• pp.294-301
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• 2004

This paper presents a combination of optimization concept and congestion control for multicast communications to bring best benefit for the network. For different types of Internet services, there will be different utility functions and so there will be different ways to choose on how to control the congestion, especially for real time multicast traffic. Our proposed algorithm OMCC brings the first implementation experiment of utility-based Multicast Congestion Control. Simulation results show that OMCC brings better network performances in multicast session throughput while it still keeps a certain fairness of unicast and multicast sessions, and thus, provides better benefit for all network participants.

• Journal of Communications and Networks
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• v.6 no.2
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• pp.133-146
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• 2004

Recently, many active queue management (AQM) algorithms have been proposed to address the performance degradation. of end-to-end congestion control under tail-drop (TD) queue management at Internet routers. However, these AQM algorithms show performance improvement only for limited network environments, and are insensitive to dynamically changing network situations. In this paper, we propose an adaptive queue management algorithm, called PID-controller, that uses proportional-integral-derivative (PID) feedback control to remedy these weak-Dalles of existing AQM proposals. The PID-controller is able to detect and control congestion adaptively and proactively to dynamically changing network environments using incipient as well as current congestion indications. A simulation study over a wide range of IP traffic conditions shows that PID-controller outperforms other AQM algorithms such as Random Early Detection (RED) [3] and Proportional-Integral (PI) controller [9] in terms of queue length dynamics, packet loss rates, and link utilization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9A
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• pp.916-922
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• 2007

Wireless networks (WNs) are developed and applied widely in a lot of areas. Now, a new generation of wireless networks is coming, and that is Wireless Mesh Network (WMN). At present, there are not so many researches which deal on this area. Most researches are derived from Mobile Ad hoc Networks (MANET) and WNs. In WMNs, there are some applications that require real-time delivery. To guarantee this, rate control and congestion control are needed. This problem leads to optimization issue in transport layer. In this paper, we propose a mathematical model which is applied in rate and congestion control in WNMs. From this model, we optimize rate and congestion control in WMNs by maximizing network utility. The proposed algorithm is implemented in distributed way both in links and sources.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.8
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• pp.331-339
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• 2003

In this paper, we propose an modified TCP congestion control algorithm using estimated RTT with congestion window parameter CWnd. Congestion window size is controlled with memorized RTT value on the congestion status. It can avoid occurrence of frequent congestion and reduce CWnd fluctuation. From simulation results, proposed algorithm shows great improvement on network efficiency and buffer utilization compared with original TCP algorithm.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.513-522
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• 2002

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 which TCP congestion window size is fluctuated during congestion occurred and if RTT (Round Trip Time) is increased, three duplicate ACK packets is not a correct congestion signal because congestion maybe already disappeared and the host may send more packets until receive the three duplicate ACK packets. Recently there is increasing interest in solving end-to-end congestion control using active network frameworks to improve the performance of TCP protocols. ACC (Active congestion control) is a variation of TCP-based congestion control with queue management In addition traffic modifications nay begin at the congested router (active router) so that ACC will respond more quickly to congestion than TCP variants. The advantage of this method is that the host uses the information provided by the active routers as well as the end points in order to relieve congestion and improve throughput. In this paper, we model enhanced ACC, provide its algorithm which control the congestion by using information in core networks and communications between active routers, and finally demonstrate enhanced performance by simulation.

• ETRI Journal
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• v.36 no.5
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• pp.761-771
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• 2014

Long-Term Evolution employs a hard handover procedure. To reduce the interruption of data flow, downlink data is forwarded from the serving eNodeB (eNB) to the target eNB during handover. In cellular networks, unbalanced loads may lead to congestion in both the radio network and the backhaul network, resulting in bad end-to-end performance as well as causing unfairness among the users sharing the bottleneck link. This work focuses on congestion in the transport network. Handovers toward less loaded cells can help redistribute the load of the bottleneck link; such a mechanism is known as load balancing. The results show that the introduction of such a handover mechanism into the simulation environment positively influences the system performance. This is because terminals spend more time in the cell; hence, a better reception is offered. The utilization of load balancing can be used to further improve the performance of cellular systems that are experiencing congestion on a bottleneck link due to an uneven load.