• Journal of Power Electronics
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• v.14 no.6
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• pp.1178-1188
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• 2014

This study proposes a finite-state model predictive controller to regulate the load current and balance the DC-link capacitor voltages of a four-leg neutral-point-clamped converter. The discrete-time model of the converter, DC-link, inductive filter, and load is used to predict the future behavior of the load currents and the DC-link capacitor voltages for all possible switching states. The switching state that minimizes the cost function is selected and directly applied to the converter. The cost function is defined to minimize the error between the predicted load currents and their references, as well as to balance the DC-link capacitor voltages. Moreover, the current regulation performance is improved by using a two-step prediction horizon. The feasibility of the proposed predictive control scheme for different references and loads is verified through real-time implementation on the basis of dSPACEDS1103.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.997-1005
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• 2010

Recently, there has been a growing interest in the use of WLAN technology due to its easy deployment, flexibility and so on. Examples of WLAN applications range from standard internet services such as Web access to real-time services with strict latency/throughput requirements such as multimedia video and voice over IP on wireless network environments. Fair and efficient distribution of the traffic loads among APs(Access Points) has become an important issue for improved utilization of WLAN. This paper focuses on an AP selection scheme for achieving better load balance, and hence increasing network resource utilization for each user on wireless network environments. This scheme makes use of active scan patterns and the network delay as main parameters of load measurement and AP selection. This scheme attempts to estimate the AP traffic loads by observing the up/down delay and utilize the results to maximize the link resource efficiency through load balancing. We compared the proposed scheme with the original SNR(Signal to Noise Ratio)-based scheme using the NS-2(Network Simulation.2). We found that the proposed scheme improves the throughput by 12.5% and lower the network up/down link delay by 36.84% and 60.42%, respectively. All in all, the new scheme can significantly increase overall network throughput and reduce up/down delay while providing excellent quality for voice and video services.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1996.03b
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• pp.93-100
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• 1996

In this paper, a computer simulationtechnique for the forging process having a spring-attached die was presented . The penalty rigid-thermoviscoplastic finite element method was empolyed together with an interatively force-balancing method, in which the convergence was achieved when the forming load and the spring reaction force are in equilibrium within the user-specified allowable accuracy. The force balance was controled by adjusting the velocity of the spring-attched die. th minimize the number of internations, a velocity estimating schemewas proposed. Two application examples found in the related company were given. In the first application example, the predicted metal folw lines were compared with the acturally forged ones. in the second example, a hot forging process with a spring-attached die was simulated and the analyzed results were discussed in order to investigated the effects of spring-attached dies on the metal flow lines and the forming loads.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.101-108
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• 2017

A wireless image sensor node collecting image data for environmental monitoring or surveillance requires a large amount of energy to transmit the huge amount of video data. Even though solar energy can be used to overcome the energy constraint, since the collected energy is also limited, an efficient energy management scheme for transmitting a large amount of video data is needed. In this paper, we propose a method to reduce the number of blackout nodes and increase the amount of gathered data by selecting an appropriate video coding method according to the energy condition of the node in a solar-powered wireless video sensor network. This scheme allocates the amount of energy that can be used over time in order to seamlessly collect data regardless of night or day, and selects a high compression coding method when the allocated energy is large and a low compression coding when the quota is low. Thereby, it reduces the blackout of the relay node and increases the amount of data obtained at the sink node by allowing the data to be transmitted continuously. Also, if the energy is lower than operating normaly, the frame rate is adjusted to prevent the energy exhaustion of nodes. Simulation results show that the proposed scheme suppresses the energy exhaustion of the relay node and collects more data than other schemes.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.286-289
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• 2001

This paper deals with the procedures of effective mid-term Operation Planning establishment for painting shop in shipbuilding. and develop prototype system. In general, the block painting process consists of two stages such as blasting operation for surface preparation and painting operation for paint application for blocks. Weather condition is a potent Influence on those operations. The procedures consists of four steps, Load analysis, Generate alternative simulation plan. Implementation of Allocation automation module and Compare result of each simulation plan. Explain of each step. as follows, 1.step, Load analysis measure amount of assigned workload and manhour. 2.step, simulation scheme include alterable control variable such as overtime, weather. Auto allocating module carry out feasibility of simulation plan. 3.step, Allocation automation module are composed of three algorithms, as followings: - the block allocation algorithm that determines the number of blocks to be processed each day, - the team allocation algorithm that allocates blocks to worker groups. - the block arrangement algorithm that arrange blocks in blasting and painting cells. Since the block arrangement algorithm is conducted simultaneously with the team allocation algorithm, the total structure of the operating algorithms is considered to have two phases: first, daily load balancing with capacity limit and second, team allocation considering arrangement each day 4 step, Comparing result of each simulation plan. and select best simulation plan.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.9-21
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• 2013

Tracking is a process which explores user equipment (UE) in the area of tracking in terms of cells. In this paper, two tracking schemes based on macrocell-microcell tiers in hierarchical LTE networks, PMMT and IMMT, are evaluated. In this network, UE can receive a signal from macrocells and overlapping microcells, and can be called from each macrocell or microcell-tier in the PMMT. Also, the UE can be called from the combined macrocell-tier and microcell-tier in the IMMT. Finally, we analyze the optimization of load balance between marcocell-tier and microcell-tier, and an analytical model is developed to evaluate those two arrangements.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.8
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• pp.84-97
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• 2012

In wireless sensor networks, cluster structure brings on many advantages such as load balancing, energy saving, and distributed key management, and so on. To transform a physical network into the cluster structure, sensor nodes should invoke a cluster formation protocol. During the protocol operation, if some nodes are compromised and they do not conform to the protocol, an inconsistency of membership in a cluster happen. This splits the cluster and consequently increases the number of clusters and decreases the number of members in the cluster. In this paper, we propose a scheme which well copes with such a problem. First, our scheme generates two hop clusters where hop distance between any two nodes is at most two. Besides, our scheme employs verification of two hop distant nodes to prevent the cluster split induced by compromised nodes. Last, our scheme mainly employs broadcast transmissions to reduce energy consumption of nodes. Simulation results have proven that our scheme reduces the number of clusters and more secure and energy-efficient than other scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.430-435
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• 2022

In this paper, we consider the non-orthogonal multiple access (NOMA) technique in the heterogeneous network (HetNET) consisting of a single macro base station (BS) and multiple small BSs, where the perfect successive interference cancellation is assumed for the NOMA signals. In this paper, we propose a deep learning-based user association and power allocation scheme to maximize the data rate in the NOMA-based HetNET. In particular, the proposed scheme includes the deep neural network (DNN)-based user association process for load balancing and the DNN-based power allocation process for data-rate maximization. Through the simulation assuming path loss and Rayleigh fading channels between BSs and users, the performance of the proposed scheme is evaluated, and it is compared with the conventional maximum signal-to-interference-plus-noise ratio (Max-SINR) scheme. Through the performance comparison, we show that the proposed scheme provides better sum rate performance than the conventional Max-SINR scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4023-4043
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• 2016

Network virtualization has been regarded as a core attribute of the Future Internet. In a network virtualization environment (NVE), multiple heterogeneous virtual networks can coexist on a shared substrate network. Thus, a substrate network failure may affect multiple virtual networks. In this case, it is increasingly critical to provide survivability for the virtual networks against the substrate network failures. Previous research focused on mechanisms that ensure the resilience of the virtual network. However, the resource efficiency is still important to make the mapping scheme practical. In this paper, we study the survivable virtual network embedding mechanisms against substrate link and node failure from the perspective of improving the resource efficiency. For substrate link survivability, we propose a load-balancing and re-configuration strategy to improve the acceptance ratio and bandwidth utilization ratio. For substrate node survivability, we develop a minimum cost heuristic based on a divided network model and a backup resource cost model, which can both satisfy the location constraints of virtual node and increase the sharing degree of the backup resources. Simulations are conducted to evaluate the performance of the solutions. The proposed load balancing and re-configuration strategy for substrate link survivability outperforms other approaches in terms of acceptance ratio and bandwidth utilization ratio. And the proposed minimum cost heuristic for substrate node survivability gets a good performance in term of acceptance ratio.