• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.817-824
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• 2021

The SDN(Software Defined Networking) technology, which appeared to overcome the limitations of the existing network system, resolves the rigidity of the existing system through the separation of HW and SW in network equipment. These characteristics of SDN provide wide scalability beyond hardware-oriented network equipment, and provide flexible load balancing policies in data centers of various sizes. In the meantime, many studies have been conducted to apply the advantages of SDN to data centers and have shown their effectiveness. The method mainly used in previous studies was to periodically check the server load and perform load balancing based on this. In this method, the more the number of servers and the shorter the server load check cycle, the more traffic increases. In this paper, we propose a new load balancing technique that can eliminate unnecessary traffic and manage server resources more efficiently by reporting to the controller when a specific level of load occurs in the server to solve this limitation.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.608-619
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• 2018

As distributed generation (DG) is connected to grid, there is new node-type occurring in distribution network. An efficient algorithm is proposed in this paper to calculate power flow for weakly meshed distribution network with DGs in different load models. The algorithm respectively establishes mathematical models focusing on the wind power, photovoltaic cell, fuel cell, and gas turbine, wherein the different DGs are respectively equivalent to PQ, PI, PQ (V) and PV node-type. When dealing with PV node, the algorithm adopts reactive power compensation device to correct power, and the reactive power allocation principle is proposed to determine reactive power initial value to improve convergence of the algorithm. In addition, when dealing with the weakly meshed network, the proposed algorithm, which builds path matrix based on loop-analysis and establishes incident matrix of node voltage and injection current, possesses good convergence and strong ability to process the loops. The simulation results in IEEE33 and PG&G69 node distribution networks show that with increase of the number of loops, the algorithm's iteration times will decrease, and its convergence performance is stronger. Clearly, it can be effectively used to solve the problem of power flow calculation for weakly meshed distribution network containing different DGs.

• Journal of Information Processing Systems
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• v.7 no.1
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• pp.53-62
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• 2011

With the steady growth of mobile technology and applications, demand for more storage in mobile devices has also increased. A lightweight block-level protocol, Internet Advanced Technology Attachment (iATA), has been developed to deliver a cost-effective storage network solution for mobile devices to obtain more storage. This paper seeks to contribute to designing and implementing Load Balancing (LB), Network Monitoring (NM) and Write Replication (WR) modules to improve the protocol's scalability and data availability. LB and NM modules are invoked to collect system resources states and current network status at each associate node (server machine). A dynamic weight factor is calculated based on the collected information and sent to a referral server. The referral server is responsible to analyze and allocate the most ideal node with the least weight to serve the client. With this approach, the client can avoid connecting to a heavily loaded node that may cause delays in subsequent in-band I/O operations. Write replication is applied to the remaining nodes through a WR module by utilizing the Unison file synchronization program. A client initially connected to node IP A for write operations will have no hindrances in executing the relevant read operations at node IP B in new connections. In the worst case scenario of a node crashing, data remain recoverable from other functioning nodes. We have conducted several benchmark tests and our results are evaluated and verified in a later section.

• Smart Structures and Systems
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• v.28 no.6
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• pp.799-810
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• 2021

When monitoring the structural integrity of a bridge using data collected through accelerometers, identifying the profile of the load exerted on the bridge from the vehicles passing over it becomes a crucial task. In this study, the speed and location of vehicles on the deck of a bridge is reconfigured using real-time video to implicitly associate the load applied to the bridge with the response from the bridge sensors to develop an image-based deep learning network model. Instead of directly measuring the load that a moving vehicle exerts on the bridge, the intention in the proposed method is to replace the correlation between the movement of vehicles from CCTV images and the corresponding response by the bridge with a neural network model. Given the framework of an input-output-based system identification, CCTV images secured from the bridge and the acceleration measurements from a cantilevered beam are combined during the process of training the neural network model. Since in reality, structural damage cannot be induced in a bridge, the focus of the study is on identifying local changes in parameters by adding mass to a cantilevered beam in the laboratory. The study successfully identified the change in the material parameters in the beam by using the deep-learning neural network model. Also, the method correctly predicted the acceleration response of the beam. The proposed approach can be extended to the structural health monitoring of actual bridges, and its sensitivity to damage can also be improved through optimization of the network training.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.1984-1986
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• 1998

This paper presents an optimal efficiency control for the inverter fed induction machine system using neural network. The motor speed and the load torque vary the efficiency characteristics of an induction motor. The optimal slip frequency has nonlinearity varied by the load torque as well as the motor speed. The induction motor is driven using the inverter system and the indirect vector control method which input is slip frequency. The neural network for estimating the optimal slip frequency has two input layer(the motor speed and the load torque) and one output layer(the optimal slip frequency that minimize the input power). Learning algorithm of the neural network is the back-propagation. Using the equivalent circuit including the nonlinearity of the induction motor, the loss reduction is analyzed quantitatively. Experimental results are shown noticeable power savings by proposed scheme in high speed and light load conditions.

• Journal of Communications and Networks
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• v.4 no.3
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• pp.230-245
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• 2002

Usually the network-throughput maximization problem for constant-bit-rate (CBR) circuit-switched traffic is posed for a fixed offered load profile. Then choices of routes and of admission control policies are sought to achieve maximum throughput (usually under QoS constraints). However, similarly to the notion of channel “capacity,” it is also of interest to determine the “network capacity;” i.e., for a given network we would like to know the maximum throughput it can deliver (again subject to specified QoS constraints) if the appropriate traffic load is supplied. Thus, in addition to determining routes and admission controls, we would like to specify the vector of offered loads between each source/destination pair that “achieves capacity.” Since the combined problem of choosing all three parameters (i.e., offered load, admission control, and routing) is too complex to address, we consider here only the optimal determination of offered load for given routing and admission control policies. We provide an off-line algorithm, which is based on Lagrangian techniques that perform robustly in this rigorously formulated nonlinear optimization problem with nonlinear constraints. We demonstrate that significant improvement is obtained, as compared with simple uniform loading schemes, and that fairness mechanisms can be incorporated with little loss in overall throughput.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.3
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• pp.13-19
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• 2016

Element-focused network analysis method for truss structure is proposed. The propagation process of loads from external loads to connected other elements is similar to that of connections between nodes in accordance with attachment rule in a network. Here nodes indicate elements in a truss structure and edges represent propagated loads. Therefore, the flows of loads in a truss structure can be calculated using the network analysis method, and consequently the structure can also be analyzed. As a first step to analyze a truss structure as a network, we propose a local load transfer rule in accordance with the topology of elements, and then analyze the loads of the truss elements. Application of this method reveal that the internal loads and reactions caused by external loads can be accurately estimated. Consequently, truss structures can be considered as networks and network analysis method can be applied to further complex truss structures.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.295-300
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• 2010

Recent researches of network structure are moving to high-level networks because there are already many research results of low-level network. Especially, current network services has been changed to the multimedia service using multicast routing such as IPTV(Internet Protocol Television) service. And then previous multicast services were provider oriented. So previous multicast structures were organized server/client model. But future multicast services will make user oriented services. Therefore there will be many service providers in the future. At this point, we study P2P network for supporting multi provider. So we research load balancing and contents lookup protocols in P2P network. In this paper, we propose network protocol and system based on super peer P2P for load balancing and efficiently service search. And we considered mobile environment for mobile IPTV.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.101-106
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• 2016

A femtocell network has been attracting attention as a promising solution for providing high data rate transmission over the conventional cellular network in an indoor environment. In this paper, we propose a distributed power control algorithm considering both indoor coverage and data load balancing in the femtocell network. As data traffic varies by time and location according to user distribution, each femto base station suffers from an unbalanced data load, which may degrade network performance. To distribute the data load, the base stations are required to adjust their transmission power dynamically. Since there are a number of base stations in practice, we propose a distributed power control algorithm. In addition, we propose the simple algorithm to detect the faulty base station and to recover coverage. We also explain how to insert a new base station into a deployed network. We present the simulation results to evaluate the proposed algorithms.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.419-429
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• 2013

The Wireless sensor network(WSN) consisting of a large number of sensors aims to gather data in a variety of environments. The sensor nodes operate on battery of limited power. so, To extend network life time is major goals of research in the WSN. In this paper, we state the key point of a energy consumption with minimum&load balancing. The proposed protocol guarantee balance of number of cluster member nodes using the node memory threshold and optimization of distribution of cluster head using the optimized clustering method. The results show that the proposed protocol could support the load balancing and high energy efficiency by distributing the clusters with a reasonable number of member nodes. The simulation results show that our schme ensure longer life time in WSN as compare with existing schemes such as LEACH and CBLM.