• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.301-303
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• 2000

This paper presents Kohonen neural network and wavelet transform analysis based technique for industrial peak load forecasting for the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a six-scale synthesis technique.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

• The KIPS Transactions:PartC
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• v.13C no.5 s.108
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• pp.621-626
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• 2006

A mobile ad hoc network (MANET) is an infrastructureless network that supports multi-hop communication. For the MANET nodes wishing to communicate with nodes in the wired Internet, the global Internet connectivity is required and this functionality can be achieved with the help of the Internet gateway. For the support of reliability and flexibility, multiple Internet gateways can be provisioned for a MANET. In this case, load-balancing becomes one of the important issues since the network performance such as the network throughput can be improved if the loads of the gateways are well-balanced. In this paper, we categorize the load-balancing mechanisms and propose a new metric for load-balancing. Simulation results show that our proposed mechanism using the hop distance and the number of routing table entries as a load-balancing metric enhances the overall network throughput.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.83-90
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• 2009

Since traffic is aggregated to a MPP that acts as an Internet gateway, if traffic load is not balanced among the MPPs in a WMN, the overall performance of a WMN becomes poor even though the total traffic load is far below the capacity of the WMN. Therefore, in this paper, we propose a stochastic load balancing scheme where each MP (Mesh Point) probabilistically selects its serving MPP according to the congestion levels of MPPs. Through extensive simulations using ns-2, we have verified that our scheme can stabilize a WMN fast when congestion occurs and reduce packet loss rate by distributing traffic load of a congested MPP to multiple MPPs in the inverse proportional to their congestion levels. Compared to queue-based load balancing scheme, our method can decrease network stabilization time by 34 seconds, and reduce packet loss rate by 7.6%. Since the proposed scheme can reduce network stabilization time by efficiently using network resource, it is expected to contribute to the reliable operation of a WMN.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1608-1614
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• 2014

Power demand forecasting is an important factor of the peak management. This paper deals with the 15 minutes ahead load forecasting problem in a DC urban railway system. Since supplied power lines to trains are connected with parallel, the load characteristics are too complex and highly non-linear. The main idea of the proposed method for the 15 minutes ahead prediction is to use the daily load similarity accounting for the load nonlinearity. An Euclidean norm with weighted factors including loads of the neighbor substation is used for the similar load selection. The prediction value is determinated by the sum of the similar load and the correction value. The correction has applied the neural network model. The feasibility of the proposed method is exemplified through some simulations applied to the actual load data of Incheon subway system.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1251-1264
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• 2018

The systematic and effective design method of a Class-D current-source resonant inverter for use in an induction cooker with zero-ripple line current is presented. The design procedure is based on the principle of the Class-D current-source resonant inverter with a simplified load network model that is a parallel equivalent circuit. An induction load characterization is obtained from a large-signal excitation test-bench based on parallel load network, which is the key to an accurate design for the induction cooker system. Accordingly, the proposed scheme provides a systematic, precise, and feasible solution than the existing design method based on series-parallel load network under low-signal excitation. Moreover, a zero-ripple condition of utility-line input current is naturally preserved without any extra circuit or control. Meanwhile, a differential-mode input electromagnetic interference (EMI) filter can be eliminated, high power quality in utility-line can be obtained, and a standard-recovery diode of bridge-rectifier can be employed. The step-by-step design procedure explained with design example. The devices stress and power loss analysis of induction cooker with a parallel load network under large-signal excitation are described. A 2,500-W laboratory prototype was developed for $220-V_{rms}/50-Hz$ utility-line to verify the theoretical analysis. An efficiency of the prototype is 96% at full load.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1087-1094
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• 2023

Due to the development of technologies, such as big data, cloud, IoT, and AI, The high data throughput is required, and the importance of network flexibility and scalability is increasing. However, existing network systems are dependent on vendors and equipment, and thus have limitations in meeting the foregoing needs. Accordingly, SDN technology that can configure a software-centered flexible network is attracting attention. In particular, a load balancing method based on SDN can efficiently process massive traffic and optimize network performance. In the existing load balancing studies in SDN environment have limitation in that unnecessary traffic occurs between servers and controllers or performing load balancing only after the server reaches an overload state. In order to solve this problem, this paper proposes a method that minimizes unnecessary traffic and appropriate load balancing can be performed before the server becomes overloaded through a method of assigning weights to servers in stages according to server load.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.279-282
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• 2007

Typically a wireless sensor network consists of a number of nodes that sense surrounding environment and collaboratively work to process and route the sensing data to a sink or gateway node. We propose an architecture with support of multiple routers in IPv6-based Low-power Wireless Personal Area Network (6LoWPAN). Our architecture provides traffic load balancing and increases network lifetime as well as self-healing mechanism so that in case of a router failure the network still can remain operational. Each router sends its own Router Advertisement message to nodes and all the nodes receiving the messages can select which router is the best router with the minimum hop-count and link information. We have implemented the architecture and assert our architecture helps in traffic load balancing and reducing data transmission delay for 6LoWPAN.

• The KIPS Transactions:PartC
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• v.18C no.1
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• pp.31-44
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• 2011

The applicability of network-based computing depends on the availability of the underlying network bandwidth. Such a growing gap between the capacity of the backbone network and the end users' needs results in a serious bottleneck of the access network in between. As a result, ISP incurs disadvantages in their business. If this situation is known to ISP in advance, or if ISP is able to predict traffic volume end-to-end link high-load zone, ISP and end users would be able to decrease the gap for ISP service quality. In this paper, simulation tools, such as ACE, ADM, and Flow Analysis, were used to be able to perceive traffic volume prediction and end-to-end link high-load zone. In using these simulation tools, we were able to estimate sequential transaction in real-network for e-Commerce. We also imported virtual network environment estimated network data, and create background traffic. In a virtual network environment like this, we were able to find out simulation results for traffic volume prediction and end-to-end link high-load zone according to the increase in the number of users based on virtual network environment.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.29-31
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• 1993

This paper presents Neural Network(NN) approach to short-term load forecasting. Input to the NN are past loads and the output is the predicted load for a given day. The NN is used to learn the relationship among past, current and future temperature and loads. Three different cases are presented. Case 1 divides into weekday and weekendday load pattern. Case 2 forcasts 24-hour ahead load. Case 3 searchs for the same load pattern as present load pattern in past load pattern. From result of forecasting, an average absolute percentage errors of case 1 shows 2.0%. That of case 2 shows 2.2, and That of case 3 shows 1.6%.