• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2B
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• pp.105-116
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• 2003

The differentiated service architecture is based on a simple model by applying a per-class service in the core node of the network. However, due to the simplified network behavior, the network structure and provisioning were more complicated. If a service provider wants the dynamic provisioning or better bandwidth guarantee, signaling protocol with QoS parameters or admission control method should be deployed in DiffServ network. However, these methods increase the complexity. Therefore, we proposed DPM2 mechanism for admission control in the DiffServ network. In this paper, we describe and survey the admission control methods that are applicable to IP networks and propose also the dynamic provisioning mechanism based on the bandwidth broker and distributed measurement based admission control and movable boundary bandwidth management to support heterogeneous QoS services in differentiated service networks. For the performance evaluation for proposed mechanism, we used ns-2 simulator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6B
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• pp.358-366
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• 2007

Recently, FCC(Federal Communications Commission) has considered for that unlicensed device leases licensed devices' channel to overcome shortage of communication channels. Therefore, IEEE 802.22 WRAN(Wireless Regional Area Networks) working group progresses CR (Cognitive Radio) technique that is able to sense and adopt void channels that are not being occupied by the licensed devices. Channel selection is of the utmost importance because it can affect the whole system performance in CR network. Thus, we propose a policy-based dynamic channel selection architecture for cognitive radio network to achieve an efficient communication. We propose three kinds of method for channel selection; the first one is weighted channel selection, the second one is sequential channel selection, and the last one is combined channel selection. We can obtain the optimum channel list and allocates channels dynamically using the proposed protocol.

• The Journal of Korean Association of Computer Education
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• v.18 no.6
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• pp.71-79
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• 2015

In a new era of Cloud and Big data, how to search the useful data from dynamic huge data pool in a right time and right way is most important at the stage where the information is getting more important. Above all, in the era of s Big Data it is required to design the advanced efficient intelligent Knowledge system which can process the dynamic variable big data. Accordingly in this paper we propose Dynamic personal Knowledge Network as one of the advanced Intelligent system approach. Adopting the human brain function and its neuro dynamics, an Intelligent system which has a structural flexibility was designed. For Structure-Function association, a personal Knowledge Network is made to be structured and to have reorganizing function as connecting the common nodes. We also design this system to have a reasoning process in the extracted optimal paths from the Knowledge Network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.715-723
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• 2015

In this paper, we propose a context-awareness routing algorithm DDV (Dynamic Direction Vector)-hop algorithm in Mobile Ad Hoc Networks. The existing algorithm in MANET, it has a vulnerability that the dynamic network topology and the absence of network expandability of mobility of nodes. The proposed algorithm performs cluster formation using a range of direction and threshold of velocity for the base-station, we calculate the exchange of the cluster head node probability using the direction and velocity for maintaining cluster formation. The DDV algorithm forms a cluster based on the cluster head node. As a result of simulation, our scheme could maintain the proper number of cluster and cluster members regardless of topology changes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.4
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• pp.463-468
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• 2007

Some network equipments made in Korea were exposed to severe earthquake in Japan several years ago. More than a hundred slim base transfer network stations had been seized with the severe earthquake at Nigata and it was reported that less than fifteen sets showed blackout by interruption of electricity, not by the structural failure. The purpose of this paper is to check the structural safety of the network equipments by performing table test, and the static and dynamic finite element analysis. For the dynamic test, the station weighing 200 kg was subjected to the Zone 3 earthquake loading of GR-63-CORE on the shaking table to obtain the dynamic responses to compare with the analysis results. It is shown that the FE analysis results are a little bit larger than that of the experimental values. And the sensitivity analysis and optimization for the natural frequency is performed and it is found that the first natural frequency is sensitive to small design change as shown in the results. And the dynamic response of optimized design is less than the original design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5723-5743
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• 2018

The evolving internet-based services demand high-speed data transmission in conjunction with scalability. The next generation optical network has to exploit artificial intelligence and cognitive techniques to cope with the emerging requirements. This work proposes a novel way to solve the dynamic provisioning problem in optical network. The provisioning in optical network involves the computation of routes and the reservation of wavelenghs (Routing and Wavelength assignment-RWA). This is an extensively studied multi-objective optimization problem and its complexity is known to be NP-Complete. As the exact algorithms incurs more running time, the heuristic based approaches have been widely preferred to solve this problem. Recently the software-defined networking has impacted the way the optical pipes are configured and monitored. This work proposes the dynamic selection of path computation algorithms in response to the changing service requirements and network scenarios. A software-defined controller mechanism with a novel packet matching feature was proposed to dynamically match the traffic demands with the appropriate algorithm. A software-defined controller with Path Computation Element-PCE was created in the ONOS tool. A simulation study was performed with the case study of dynamic path establishment in ONOS-Open Network Operating System based software defined controller environment. A java based NOX controller was configured with a parent path computation element. The child path computation elements were configured with different path computation algorithms under the control of the parent path computation element. The use case of dynamic bulk path creation was considered. The algorithm selection method is compared with the existing single algorithm based method and the results are analyzed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.809-817
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• 2020

In the design and development process of Small-Sat power distribution and transmission module, the stability of dynamic resources was evaluated by a deep learning algorithm. The requirements for the stability evaluation consisted of the power distribution function of the power distribution module and demand module to the SAR radar in Small-Sat. To verify the performance of the switching power components constituting the power module PDM, the reliability was verified using a dynamic neural network. The adoption material of deep learning for reliability verification is the power distribution function of the payload to the power supplied from the small satellite main body. Modeling targets for verifying the performance of this function are output voltage (slew rate control), voltage error, and load power characteristics. First, to this end, the Coefficient Structure area was defined by modeling, and PCB modules were fabricated to compare stability and reliability. Second, Levenberg-Marquare based Two-Way NARX neural network Sigmoid Transfer was used as a deep learning algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3602-3620
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• 2016

Dynamic topology is one of the main influence factors on network performability. However, it was always ignored by the traditional network performability assessment methods when analyzing large-scale mobile ad hoc networks (MANETs) because of the state explosion problem. In this paper, we address this problem from the perspective of complex network. A two-layer hierarchical modeling approach is proposed for MANETs performability assessment, which can take both the dynamic topology and multi-state nodes into consideration. The lower level is described by Markov reward chains (MRC) to capture the multiple states of the nodes. The upper level is modeled as a small-world network to capture the characteristic path length based on different mobility and propagation models. The hierarchical model can promote the MRC of nodes into a state matrix of the whole network, which can avoid the state explosion in large-scale networks assessment from the perspective of complex network. Through the contrast experiments with OPNET simulation based on specific cases, the method proposed in this paper shows satisfactory performance on accuracy and efficiency.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.39-46
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• 1998

In this paper, we present a neural network identification and a control of highly complicated nonlinear left ventricular assist device(LVAD) system with a pneumatically driven mock circulation system. Generally, the LVAD system needs to compensate for nonlinearities. It is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with neural network identification(NNI). Once the NNI has learned the dynamic model of the LVAD system, the other network, called neural network controller(NNC), is designed for a control of the LVAD system. The ability and effectiveness of identifying and controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.511-524
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• 2016

The Virtual Local Area Network (VLAN) has been used for a long time in campus and enterprise networks as the most popular network virtualization solution. Due to the benefits and advantages achieved by using VLAN, network operators and administrators have been using it for constructing their networks up until now and have even extended it to manage the networking in a cloud computing system. However, their configuration is a complex, tedious, time-consuming, and error-prone process. Since Software Defined Networking (SDN) features the centralized network management and network programmability, it is a promising solution for handling the aforementioned challenges in VLAN management. In this paper, we first introduce a new architecture for campus and enterprise networks by leveraging SDN and OpenFlow. Next, we have designed and implemented an application for easily managing and flexibly troubleshooting the VLANs in this architecture. This application supports both static VLAN and dynamic VLAN configurations. In addition, we discuss the hybrid-mode operation where the packet processing is involved by both the OpenFlow control plane and the traditional control plane. By deploying a real test-bed prototype, we illustrate how our system works and then evaluate the network latency in dynamic VLAN operation.