• 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.

• Journal of IKEEE
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• v.16 no.1
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• pp.45-50
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• 2012

This paper proposes the methodology to estimate the routing congestion of modern IC quickly and accurately at the early stage of the design flow. The occurrence of over-congestion in the routing process causes routing failure which then takes unnecessary time to re-design the physical design from the beginning. The precise estimation of routing congestion at the early design stage leads to a successful physical design that minimizes over-congestion which in turn reduces the total design time cost. The proposed estimation method at the block-level floorplan stage measures accurate routing congestion by using the analyzed virtual interconnections of inter/intra blocks, synthesized virtual power/ground and clock networks.

• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.27-38
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• 2002

This study estimates the social cost of the traffic congestion of the Express highway from Seoul to Pusan during the New Year holiday in 1999. Considering inelastic demand and the hyper congestion, we show the congestion cost can be estimated as externalities caused by traffics which exceed the road capacity. Due to the congestion, it is estimated that it took about 12.40 hours more from Seoul to Pusan. The congestion is also estimated to have caused fuel cost of 0.6 billion won. time cost of 43.6 billion won and environmental cost of 0.5 billion won. The total cost reached up to 44.8 billion won.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.3
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• pp.131-137
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• 2014

It is expected that there will be delay of scheduled transmission network reinforcement and huge investment of renewable energy resources in Korea. As transmission capacity expansion delayed, supplying power to Seoul metropolitan area will not be increased as scheduled. In addition, uncertain renewable energy out of Seoul metropolitan area can cause transmission congestion in the future power system. These two combining effects will make the difference in locational marginal prices(LMP) and congestion costs increase. In that sense, this paper will analyze how much the congestion costs for Korea power system are incurred in the future power system. Most of previous approaches to analyze the congestion costs for electric power system are based on the optimal power flow model which cannot deal with hourly variation of power system. However, this study attempted to perform the analysis using market simulation model(M-Core) which has the capability of analyzing the hourly power generation cost and power transmission capacity, and market prices by region. As a result, we can estimate the congestion costs of future power system considering the uncertainty of renewable energy and transmission capacity.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.641-648
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• 2012

The up-streams of the continuous streaming of data packets with lower importance level in the wireless sink node can cause congestion and delay, they affect on energy efficiency, memory size, buffer size, and throughput. This paper proposes a new wireless sink congestion control mechanism based on tournament scheduling. The proposed method consists of two module parts: stream decision module part and service differentiation module part. The final winner in the tournament controls congestion effectively, minimizes packet loss due to congestion, decreases energy consumption, and improves QoS. The simulation result shows that the proposed method is more effective and has better performance compared with those of congestion descriptor-based control method, reliability-based control method, and best-effort transmission control method.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.127-132
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• 2002

This paper aims to adjust the window size according to the network condition that the sender determines by making the receiver participating in the congestion levels. TCP-RLDM has the measurement-based transmission strategy based on the data-receiving rate complementing TCP with the property of Additive Increase / Multiplicative Decrease. The protocol can make an performance improvement by responding differently according to the property of errors-whether congestion losses or transient transmission errors - to confront dynamically in heterogeneous environments with wired or wireless networks and delay-sensitive or -tolerant applications. By collecting data-receiving rate and the cause of errors from the receiver and by enabling sender to use the congestion avoidance strategy before occuring congestion possibly, the protocol works well at variable network environments.

• International Journal of Highway Engineering
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• v.16 no.4
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• pp.127-134
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• 2014

PURPOSES : To operate more efficient traffic management system, it is utmost important to detect the change in congestion level on a freeway segment rapidly and reliably. This study aims to develop classification method of congestion change type. METHODS: This research proposes two classification methods to capture the change of the congestion level on freeway segments using the dedicated short range communication (DSRC) data and the vehicle detection system (VDS) data. For developing the classification methods, the decision tree models were employed in which the independent variable is the change in congestion level and the covariates are the DSRC and VDS data collected from the freeway segments in Korea. RESULTS : The comparison results show that the decision tree model with DSRC data are better than the decision tree model with VDS data. Specifically, the decision tree model using DSRC data with better fits show approximately 95% accuracies. CONCLUSIONS : It is expected that the congestion change type classified using the decision tree models could play an important role in future freeway traffic management strategy.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.820-831
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• 2015

In a deregulated electricity market, congestion of the transmission lines is a major problem the independent system operator (ISO) would face. Rescheduling of generators is one of the most practiced techniques to alleviate the congestion. However, not all generators in the system operate deterministically and independently, especially wind power generators (WTGs). Therefore, a novel optimal rescheduling model for congestion management that accounts for the uncertain and correlated power sources and loads is proposed. A probabilistic power flow (PPF) model based on 2m+1 point estimate method (PEM) is used to simulate the performance of uncertain and correlated input random variables. In addition, the impact of direct electricity purchase contracts on the congestion management has also been studied. This paper uses artificial bee colony (ABC) algorithm to solve the complex optimization problem. The proposed algorithm is tested on modified IEEE 30-bus system and IEEE 57-bus system to demonstrate the impacts of the uncertainties and correlations of the input random variables and the direct electricity purchase contracts on the congestion management. Both pool and nodal pricing model are also discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.186-191
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• 2011

Ramp metering has been used to solve recurrent or non-recurrent congestion on many highways. However, the existing ramp metering methods cannot control non-recurrent congestion like incident and don't have any methods to solve congestion after congestion. In addition, the methods cannot solve congestion quickly because ramp metering operates independently for each ramp. In this study, we developed SARAM which is ramp metering technique with shockwave theory in order to solve the problems. In simulation from Jangsoo IC to Joongdong IC, we confirmed that speed increased by 7.32km/h and delay time reduced by 39.14sec.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.609-611
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• 2003

This paper presents a method for a congestion management in the competitive market which is modeled as the multiple bilateral transaction. Traditionary, the congestion management for the multiple bilateral transaction is accomplished through the process of adjustment bids. It is necessary in for the market entity to submit their price information when the congestion is occured. Finally, the ISOs can be blown about the approximated contract price of participants from the price of adjustment bids. However, the entities can submit only the amount of their contract to ISOs and ISOs are required the method to manage the congestion only by the contracted quantity. Therefore, this paper presents a method for congestion management by curtailing the only contracted quantity of market entities. To evaluated the above problem, we suggest Bilateral Transaction Distribution Factors(BTDFs), which is the sensitivity of line flow with curtailment of transactions. Using this factor, we studied about congestion management when the objective function is to minimize total curtailment of transaction.