• Journal of KIISE:Information Networking
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• v.29 no.5
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• pp.573-582
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• 2002

We propose centralized server based QoS routing schemes, where a route server is responsible for determining QoS paths on behalf of all the routers in a routing domain. In the proposed server based schemes, the dynamic link QoS state information, which is required for a QoS path computation, is implicitly maintained at route server as it assigns or gets back QoS paths. By maintaining the network state information this way, we may not only eliminate the overhead to exchange network state update message but also achieve higher routing performance by utilizing accurate network state information in path computation. We discuss path caching techniques for reducing the amount of path computation overhead at the route server, and evaluate the performance of the proposed schemes using simulation. The simulation results show that the path caching schemes may significantly reduce the route server load. The proposed schemes are also compared to the distributed QoS routing schemes proposed in the literature. It has been shown that the proposed server based schemes not only enhance the routing performance, but they are also competitive with respect to routing overheads.

• Journal of Communications and Networks
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• v.7 no.2
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• pp.178-191
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• 2005

Fourth-generation (4G) wireless networks will be the IP-based cellular networks integrating Internet with the existing cellular networks. Two important issues should be concerned in the IP-based cellular networks, IP mobility, and quality-of-service (QoS) guarantees. In this paper, we proposed two mechanisms to solve the problems with IP mobility and RSVP-based QoS provisioning. First, virtual-IP (VIP) allocation scheme in areas with a large rate of handoff can minimize the wireless signaling overhead due to IP mobility. The access routers (ARs) create dynamically the VIP zone by using the measured handoff rate derived from the history of the handoff into neighboring ARs. We show that VIP allocation scheme reduces the binding update messages in the wireless link than hierarchical mobile IPv6. Second, the new advance resource reservation protocol called proportional aggregate RSVP (PA-RSVP) can minimize waste of bandwidth and soft state refresh overhead due to IP mobility. It allocates the bandwidth in advance between the mobility anchor point and neighboring ARs using proportional aggregate reservation. We also show that PA-RSVP provides an improved performance over existing protocols.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.4
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• pp.411-419
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• 2005

In this paper, a sliding mode observer for solar array current estimation in the photovoltaic power generation system is presented. The solar array current estimation Information is obtained from the sliding mode observer and fed into the maximum power point tracker to update the reference voltage. The parameter values such as inverter dc link capacitances cm be changed up to 50$\%$ from their nominal values and the linear observer can't estimate the correct state values under the parameter variations and noisy environments. The configuration of sliding mode observer is simple, but it shows the robust tracking performance against parameter variations and modeling uncertainties. In this paper, the method for constructing the sliding mode observer using equivalent control input is presented and the convergence of the proposed observer is verified by the Lyapunov method. The mathematical modeling and the experimental results verify the validity of the proposed method.

• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.213-225
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• 2009

A stationary Markov chain model is a stochastic process with the Markov property. Having the Markov property means that, given the present state, future states are independent of the past states. The Markov chain model has been widely used for water resources design as a main tool. A main assumption of the stationary Markov model is that statistical properties remain the same for all times. Hence, the stationary Markov chain model basically can not consider the changes of mean or variance. In this regard, a primary objective of this study is to develop a model which is able to make use of exogenous variables. The regression based link functions are employed to dynamically update model parameters given the exogenous variables, and the model parameters are estimated by canonical correlation analysis. The proposed model is applied to daily rainfall series at Seoul station having 46 years data from 1961 to 2006. The model shows a capability to reproduce daily and seasonal characteristics simultaneously. Therefore, the proposed model can be used as a short or mid-term prediction tool if elaborate GCM forecasts are used as a predictor. Also, the nonstationary Markov chain model can be applied to climate change studies if GCM based climate change scenarios are provided as inputs.