• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1B
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• pp.154-161
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• 2010

In wireless sensor networks, due to the many-to-one convergence of upstream traffic, congestion more probably appears. The existing congestion control protocols avoid congestion by controlling incoming traffic, but the duty-cycle operation of MAC(Medium Access Control) layer has not considered. In this paper, we propose DCA(Duty-cycle Based Congestion Avoidance), an energy efficient congestion control scheme using duty-cycle adjustment for wireless sensor networks. The DCA scheme uses both a resource control approach by increasing the packet reception rate of the receiving node and a traffic control approach by decreasing the packet transmission rate of the sending node for the congestion avoidance. Our results show that the DCA operates energy efficiently and achieves reliability by its congestion control scheme in duty-cycled wireless sensor networks.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.465-466
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• 2009

This paper investigates congestion detection and control strategies for multi-path traffic (CDCM) diss emination in lifetime-constrained wireless sensor networks. CDCM jointly exploits packet arrival rate, succ essful packet delivery rate and current buffer status of a node to measure the congestion level. Our objec tive is to develop adaptive traffic rate update policies that can increase the reliability and the network lif etime. Our simulation results show that the proposed CDCM scheme provides with good performance.

• Journal of IKEEE
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• v.21 no.2
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• pp.115-122
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• 2017

In vehicular safety service, every vehicle broadcasts Basic Safety Message (BSM) periodically to inform neighbor vehicles of host vehicle information. However, this can cause network congestion in a region that is crowded with vehicles resulting in a reduction in the message delivery ratio and an increase in the end-to-end delay. Therefore, it could destabilize the vehicular safety service system. In this paper, in order to improve the congestion control and to consider the hidden node problem, we propose a congestion control scheme using entire network congestion level estimation combined with transmission power control, data rate control and time slot based transmission control algorithm. The performance of this scheme is evaluated using a Qualnet network simulator. The simulation result shows that our scheme mitigates network congestion in heavy traffic cases and enhances network capacity in light traffic cases, so that packet error rate is perfectly within 10% and entire network load level is maintained within 60~70%. Thus, it can be concluded that the proposed congestion control scheme has quite good performance.

• Journal of Advanced Navigation Technology
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• v.17 no.2
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• pp.218-224
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• 2013

Uplink overflow in WMSN (Wireless Multimedia Sensor Networks) aggravates the resource consumption, delay, and traffic congestion. This paper proposes a new traffic congestion control mechanism using popularity. The proposed mechanism controls congestions by dispersing the media traffic, and it control fairly packets according to priority. This paper proposes PQS (Packet Queue Scheduler) to control fairly packets, and the proposed mechanism provides a fair opportunity to all sensor nodes without a specific location. The simulation results show that the proposed mechanism achieves improved performance in throughput, delay ratio, link quality, and buffer queue control ratio compared with those of other existing methods.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.30-44
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• 2013

Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.

• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.51-60
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• 2003

One of the most important matters in designing network and realizing service, is to grip on the traffic characteristics. Conventional traffic prediction and analysis used the models which based on the Poisson or Markovian. Recently, experimental research on the LAN, WAN and VBR traffic properties have been pointed rut that they weren't able to display actual real traffic specificities because the models based on the Poisson assumption had been underestimated the long range dependency of network traffic and self-similar peculiarities, it has been lately presented that the new approach method using self-similarity characteristics as similar as the real traffic models. Therefore, in this paper, we generated self-similar data traffic like real traffic as background load. On the existing ABR congestion control algorithm, we analyzed by classify into ACR, buffer utilization. cell drop rate, transmission throughput with the representative EFCI, ERICA, EPRCA and NIST twitch algorithm to show the efficient reaction about the burst traffic.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.29-38
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• 1998

This ppaer suggests a congestion control scheme for CL(ConnectionLess) overlay network using the feedback loops getween CL werver, between CL servers, and the header translation table of CL server. The CL overlay network for CBDS(Connectionless Broadband Data Service) defined by ITU0T(International Telecommunication Union-Telecommunication) consists of CL servers which route frames and links which connect between CL user and CL server or between CL servers. In this CL overlay network, two kinds of congestions, link congestion and CL server congestion, may occur. We suggest a scheme that can solve the congestion using ABR(Available Bit Rate) feedback control loop, the traffic control mechanism. This scheme is the link-by-link method suing the ABR feedback control loops between CL user and CL server or between CL servers, and the header translation table of CL server. As CL servers are always endpoints of ABR connections, the congestion staturs of the CL server can be informed to the traffic sources using RM(Resource Management) cell of the ABR feedback loops. Also CL server knows the trafffic sources making congestion by inspecting the source address field of CLNAP-PDUs(ConnectionLess Network Access Protocol - Protocol Data Units). Therefore this scheme can be implemeted easily using only both ABR feedback control loop of ATM layer and the congestion state table using the header translation table of CL server because it does not require separate feedback links for congestion control of CL servers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.762-777
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• 2014

With the increasing usage of cloud applications such as MapReduce and social networking, the amount of data traffic in data center networks continues to grow. Moreover, these appli-cations follow the incast traffic pattern, where a large burst of traffic sent by a number of senders, accumulates simultaneously at the shallow-buffered data center switches. This causes severe packet losses. The currently deployed TCP is custom-tailored for the wide-area Internet. This causes cloud applications to suffer long completion times towing to the packet losses, and hence, results in a poor quality of service. An Explicit Congestion Notification (ECN)-based approach is an attractive solution that conservatively adjusts to the network congestion in advance. This legacy approach, however, lacks scalability in terms of the number of flows. In this paper, we reveal the primary cause of the scalability issue through analysis, and propose a new congestion-control algorithm called FaST. FaST employs a novel, virtual congestion window to conduct fine-grained congestion control that results in improved scalability. Fur-thermore, FaST is easy to deploy since it requires only a few software modifications at the server-side. Through ns-3 simulations, we show that FaST improves the scalability of data center networks compared with the existing approaches.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.236-242
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• 2003

ATM ABR service controls network traffic using feedback information on the network congestion situation in order to guarantee the demanded service qualities and the available cell rates. In this paper we apply the control method using queue length prediction to the formation of feedback information for more efficient ABR traffic control. If backward node receive the longer delayed feedback information on the impending congestion, the switch can be already congested from the uncontrolled arriving traffic and the fluctuation of queue length can be inefficiently high in the continuing time intervals. The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series. The predicted congestion information is backward to the node. NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction. Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.1291-1293
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• 2007

Due to dense deployment and innumerable amount of traffic flow in wireless sensor networks (WSNs), congestion becomes more common phenomenon from simple periodic traffic to unpredictable bursts of messages triggered by external events. Even for simple network topology and periodic traffic, congestion is a likely event due to dynamically time varying wireless channel condition and contention caused due to interference by concurrent transmissions. In this paper, we have proposed three mechanisms: upstream source count and buffer based rate control and snoop based MAC level ACK scheme to avoid congestion. The simulation results show that our proposed mechanism achieves around 80% delivery ratio even under bursty traffic condition