• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6B
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• pp.508-516
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• 2006

The explosive growth of wireless network users and the existence of various wireless services have demanded high rate throughput as well as user's QoS guarantees. Towards this, this paper proposes QoS-oriented subcarrier allocation scheme considering the QoS provisioning of multiple users, which is major requirement for wireless network design point of view. This paper introduces joint RR/K&H combined with M-LWDF(Modified Largest Weighted Delay First) scheme throughout observing statistical channel behavior and real time queuing analysis for appropriate resource allocation tightly connected to multiuser scheduling. Accordingly, the system throughput can be enhanced, and the QoS demanded for delay sensitive services can be satisfied. Furthermore, the proposed scheme is applied for OFDMA(Orthogonal Frequency Division Multiple Access) systems to allocate sub-carriers in optimal way. The simulation results verify plausible performances of proposed resource allocation scheme via showing superior effective capacity under time-varying physical-layer channel behaviors.

• Journal of Digital Contents Society
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• v.19 no.8
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• pp.1545-1554
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• 2018

In order to support the mobility of the wireless devices, at least two APs (Access Points) must be arranged in a single AP area to maintain communication area. In the WLAN (Wireless LAN) environment, seamless handover is one of the most important issues in terms of effective utilization of wireless networks and maximization of services for users. On the other hand, SDN (Software-Defined Networking), which is emerging rapidly in recent years, is revolutionizing network management in terms of flexibility, fine control, and convenience. SDN originally reduces latency time or increases network robustness by real-time flow table control reducing or bypassing paths between switches in LAN-based data centers. In this study, we apply OpenFlow, a SDN platform focused on wired LAN, to a dense WLAN environment using legacy APs to implement and evaluate seamless handover for streaming services of digital contents.

• International Commerce and Information Review
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• v.9 no.2
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• pp.103-120
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• 2007

The knowledge based economy requires more and more people to learn new knowledge and skills in a timely and effective manner. These needs and new technology such as computer and Internet are fueling a transition in e-learning. According to specialist's opinion, imagination experience studying is generalized, and learning environment that language barrier by studying, multi-language studying Machine that experience past things that disappear through simulation, and travel area, and experience future changed state disappears is forecasting to come. This is previewing finally that it may become future education that education and IT, element of entertainment is combined. Already, became story that argument for party satellite of e-Learning existence passes one season already. e-Learning is utilized already in all educations that we touch by effectiveness by corporation's competitive power improvement and implement of lifelong education in educational institutions through present e-Learning. It is obvious that when see from our viewpoint which is defining e-Learning by one industry and rear by application to education as well as one new growth power about these, e-Learning industry becomes very important means that can solve dilemma of growth real form. Only, special quality of digital industry that e-Learning is being same with other digital industry and repeat putting out a fire rapidly, and is repeating sudden change that these evolution is not gradual growth of accumulation and improvement of technology that is appearing consider need to. In the meantime, we need to observe about evolution of Information Technology. Because there is some scholars who e-Learning's concept foresees to evolve by u-Learning.(although, a person who see that these concept is not more in marketing terminology by some scholars' opinion is). This u-Learning's concept means e-Learning that take advantage of ubiquitous technology as Ubiquitous-Learning's curtailment speech. Ubiquitous, user means Information-Communication surrounding that can connect to network freely regardless of place without feeling network or computer. There is controversy about introduction time regarding these direction, but e-Learning is judged to evolve by u-Learning necessarily. Because keep in step and age that study all contents that learner wants under environment of 3A (any time, any whrer, any device) by individual order thoroughly is foreseen to come in ubiquitous learning environment that approach more festinately.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1211-1216
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• 2000

Asynchronous transfer mode (ATM) can be efficiently used to transport packet data services. The switching system will support voice and packet data services simultaneously from end to end applications. To guarantee quality of service (QoS) of the offered services, source rateot send packet data is needed to control the network overload condition. Most existing control algorithms are shown to provide the threshold-based feedback control technique. However, real-time voice calls can be dynamically connected and released during data services in the network. If the feedback control information delays, quality of the serviced voice can be degraded due to a time delay between source and destination in the high speed link. An adaptive algorithm based on the optimal least mean square error technique is presented for the predictive feedback control technique. The algorithm attempts to predict a future buffer size from weight (slope) adaptation of unknown functions, which are used fro feedback control. Simulation results are presented, which show the effectiveness of the algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1238-1244
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• 2009

This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module for reducing computer calculating time and a signal generation module for simulating real time performance data are used. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. The reliability and capability of the proposed on-line diagnostic program were confirmed through application to the helicopter engine health monitoring.

• Journal of Internet Computing and Services
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• v.3 no.3
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• pp.67-74
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• 2002

Asynchronous transfer mode (ATM) can be efficiently used to transport packet data services. The switching system will support voice and packet data services simultaneously from end to end applications. To guarantee quality of service (QoS) of the offered services, source rate to send packet data is needed to control the network overload condition. Most existing control algorithms are shown to provide the threshold-based feedback control technique. However, real-time voice calls can be dynamically connected and released during data services in the network. If the feedback control information delays, quality of the serviced voice can be degraded due to a time delay between source and destination in the high speed link, An adaptive algorithm based on the optimal least mean square error technique is presented for the predictive feedback control technique. The algorithm attempts to predict a future buffer size from weight (slope) adaptation of unknown functions, which are used for feedback control. Simulation results are presented, which show the effectiveness of the algorithm.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.301-309
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• 2005

Learning program's behavior using machine learning techniques based on system call audit data is an effective intrusion detection method. Rule teaming, neural network, statistical technique, and hidden Markov model are representative methods for intrusion detection. Among them neural networks are known for its good performance in teaming system call sequences. In order to apply it to real world problems successfully, it is important to determine their structure. However, finding appropriate structure requires very long time because there are no formal solutions for determining the structure of networks. In this paper, a novel intrusion detection technique using evolutionary neural networks is proposed. Evolutionary neural networks have the advantage that superior neural networks can be obtained in shorter time than the conventional neural networks because it leams the structure and weights of neural network simultaneously Experimental results against 1999 DARPA IDEVAL data confirm that evolutionary neural networks are effective for intrusion detection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4B
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• pp.192-198
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• 2008

In this paper, we propose a scheme that improves the transmission performance of realtime multimedia data in wireless Local Area Network (LAN) environment, through the dynamical control of Transmission Opportunity (TXOP) period of the IEEE 802.11e HCCA Medium Access Control (MAC). The existing schedulers which determine the frame transmission time and its duration could not appropriately cope with the change of physical transmission rate, since the TXOP period has remained unchanged with the change of transmission rate of the wireless station. Our scheme is devised to keep the transmission performance of real-time multimedia data effectively unchanged by making TXOP period be extended when the transmission rate gets reduced. The proposed scheme is experimented along with IEEE 802.11e reference model using NCTUns simulator, which shows that the multimedia data is effectively delivered with the change of transmission rate as the distance between the wireless station and its access point increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2811-2817
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• 2010

In this paper we propose the QAC-MAC that supports Quality of Service(QoS) and saves energy resources of the sensor node, and hence prolonging the lifetime of the sensor network with multiple sink nodes. Generally, the nodes nearest to the sink node often experience heavy congestion since all data is forwarded toward the sink through those nodes. So this critically effects on the delay-constraint data traffics. QAC-MAC uses a hybrid mechanism that adapts scheduled scheme for medium access and scheduling and unscheduled scheme based on TDMA for no data collision transmission. Generally speaking, characteristics of the real-time traffic with higher priority tends to be bursty and has same destination. QAC-MAC adapts cross-layer concept to rearrange the data transmission order in each sensor node's queue, saves energy consumption by allowing few nodes in data transmission, and prolongs the network lifetime.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.633-650
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• 2013

All the imputation techniques proposed so far in literature for data imputation are offline techniques as they require a number of iterations to learn the characteristics of data during training and they also consume a lot of computational time. Hence, these techniques are not suitable for applications that require the imputation to be performed on demand and near real-time. The paper proposes a computational intelligence based architecture for online data imputation and extended versions of an existing offline data imputation method as well. The proposed online imputation technique has 2 stages. In stage 1, Evolving Clustering Method (ECM) is used to replace the missing values with cluster centers, as part of the local learning strategy. Stage 2 refines the resultant approximate values using a General Regression Neural Network (GRNN) as part of the global approximation strategy. We also propose extended versions of an existing offline imputation technique. The offline imputation techniques employ K-Means or K-Medoids and Multi Layer Perceptron (MLP)or GRNN in Stage-1and Stage-2respectively. Several experiments were conducted on 8benchmark datasets and 4 bank related datasets to assess the effectiveness of the proposed online and offline imputation techniques. In terms of Mean Absolute Percentage Error (MAPE), the results indicate that the difference between the proposed best offline imputation method viz., K-Medoids+GRNN and the proposed online imputation method viz., ECM+GRNN is statistically insignificant at a 1% level of significance. Consequently, the proposed online technique, being less expensive and faster, can be employed for imputation instead of the existing and proposed offline imputation techniques. This is the significant outcome of the study. Furthermore, GRNN in stage-2 uniformly reduced MAPE values in both offline and online imputation methods on all datasets.