• Journal of Communications and Networks
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• 제14권6호
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• pp.640-652
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• 2012

Many studies have investigated the smart grid architecture and communication models in the past few years. However, the communication model and architecture for a smart grid still remain unclear. Today's electric power distribution is very complex and maladapted because of the lack of efficient and cost-effective energy generation, distribution, and consumption management systems. A wireless smart grid communication system can play an important role in achieving these goals. In this paper, we describe a smart grid communication architecture in which we merge customers and distributors into a single domain. In the proposed architecture, all the home area networks, neighborhood area networks, and local electrical equipment form a local wireless mesh network (LWMN). Each device or meter can act as a source, router, or relay. The data generated in any node (device/meter) reaches the data collector via other nodes. The data collector transmits this data via the access point of a wide area network (WAN). Finally, data is transferred to the service provider or to the control center of the smart grid. We propose a wireless cooperative communication model for the LWMN.We deploy a limited number of smart relays to improve the performance of the network. A novel relay selection mechanism is also proposed to reduce the relay selection overhead. Simulation results show that our cooperative smart grid (coopSG) communication model improves the end-to-end packet delivery latency, throughput, and energy efficiency over both the Wang et al. and Niyato et al. models.

• 한국콘텐츠학회논문지
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• 제16권7호
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• pp.1-18
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• 2016

선행연구에 따르면 조직문화 및 조직내 커뮤니케이션이 지식경영과 조직성과에 영향을 미칠 수 있지만, 이런 모든 변인들 간의 관계를 보여주는 보다 통합적인 연구가 여전히 필요하다. 이 논문은 이러한 변인들의 상호간 관계 및 영향력을 제시함으로써, 지식경영 및 관련된 변인들을 통해 조직성과를 향상시키는 통합적인 접근방법을 개발하기 위한 다양한 방법들을 제시한다. 따라서 이 연구의 목적은 국가문화, 조직문화, 조직내 커뮤니케이션, 지식경영, 조직성과 간의 상호관계를 고찰하는 것이다. 이러한 변인들 간의 관계에 대한 종합적 문헌연구방법을 통해 상호관계가 개념적 모델로서 요약되었다. 이 모델에 의하면 조직내 커뮤니케이션, 지식경영, 조직문화는 조직성과에 영향을 미치며, 또한 조직내 커뮤니케이션과 조직문화는 지식경영에도 영향을 미친다. 이러한 개념적 모델에 기반하여, 조직성과를 최대한 향상시킬 방법을 찾고자 하는 인적자원 연구자 및 실무자들을 위한 시사점들이 제시되었다.

• 한국산림과학회지
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• 제96권4호
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• pp.377-386
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• 2007

본 연구는 커뮤니케이션 분야에서 보편적으로 사용되고 있는 정교화 가능성 모델이 산림분야에서도 적용 가능한지와 미디어간 커뮤니케이션 효과 차이를 검증하고자 하였다. 이 모델이 제시하고 있는 주요 변수인 동기변수(관여도, 인지욕구 및 감성욕구)와 능력변수(사전 지식)가 태토변화에 미치는 영향력을 회귀분석으로 검토한 결과, 대부분의 독립변수들은 유의성이 높아 산림분야도 이 모델을 적용할 수 있다는 것이 확인되었다. 미디어 효과는 TV, 인터넷 및 신문으로 동일한 메시지를 전달한 후, 미디어별 설득력과 회상의 차이로써 검증하였다. 분산분석 결과, TV가 신문보다 설득력이 있었지만 TV와 인터넷 간에는 차이가 없었다. 회상의 경우에는 인터넷과 TV가 신문보다 효과적이었다.

• 한국인쇄학회지
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• 제12권1호
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• pp.29-42
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• 1994

• 한국정보처리학회논문지
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• 제6권11호
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• pp.2845-2862
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• 1999

As the technical advances in portable computers and wireless communication technologies, mobile computing environment has been rapidly expanded. The mobile users on mobile host can access information via wireless communication from the distributed heterogeneous multidatabase system in which pre-existing independent local information systems are integrated into one logical system to support mobile applications. Hence, mobile transaction model should include not only the features for heterogeneous multidatabase systems but also the ones for mobile computing environment. In this paper, we proposed a mobile flex transaction model which extends the flexible transaction model that previously proposed for heterogeneous multidatabase systems is extended to support the requirements of mobile heterogeneous multidatabase systems. We also presented the execution control mechanism of the mobile flex transaction model. The proposed mobile flex transaction model allows the definition of location-dependent subtransactions, the effective support of hand-over, and the flexibility of transaction executions. Hence, the proposed mobile flex transaction model can be suit to mobile heterogeneous multidatabase systems that have low power capability, low bandwidth, and high communication failure possibility.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.125-130
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• 2020

At the end of 1997, the volatility of the exchange rate intensified as the nation's exchange rate system was converted into a free-floating exchange rate system. As a result, managing the exchange rate is becoming a very important task, and the need for forecasting the exchange rate is growing. The exchange rate prediction model using the existing exchange rate prediction method, statistical technique, cannot find a nonlinear pattern of the time series variable, and it is difficult to analyze the time series with the variability cluster phenomenon. And as the number of variables to be analyzed increases, the number of parameters to be estimated increases, and it is not easy to interpret the meaning of the estimated coefficients. Accordingly, the exchange rate prediction model using artificial neural network, rather than statistical technique, is presented. Using DNN, which is the basis of deep learning among artificial neural networks, and LSTM, a recurrent neural network model, the number of hidden layers, neurons, and activation function changes of each model found the optimal exchange rate prediction model. The study found that although there were model differences, LSTM models performed better than DNN models and performed best when the activation function was Tanh.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권4호
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• pp.1489-1503
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• 2018

Spectrum reuse has attracted much concern of researchers and scientists, however, the dynamic spectrum access is challenging, since an individual secondary user usually just has limited sensing abilities. One key insight is that spectrum usage forecasting among secondary users, this inspiration enables users to obtain more informed spectrum opportunities. Therefore, spectrum usage forecasting is vital to cognitive radio networks (CRNs). With this insight, a spectrum usage forecasting model for the occurrence of primary users prediction is derived in this paper. The proposed model is based on auto regressive enhanced primary user emergence reasoning (AR-PUER), which combines linear prediction and primary user emergence reasoning. Historical samples are selected to train the spectrum usage forecasting model in order to capture the current distinction pattern of primary users. The proposed scheme does not require the knowledge of signal or of noise power. To verify the performance of proposed spectrum usage forecasting model, we apply it to the data during the past two months, and then compare it with some other sensing techniques. The simulation results demonstrate that the spectrum usage forecasting model is effective and generates the most accurate prediction of primary users occasion in several cases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2450-2469
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• 2018

In this paper, we develop a spatiotemporal model to analysis of cellular user in underlay D2D communication by using stochastic geometry and queuing theory. Firstly, by exploring stochastic geometry to model the user locations, we derive the probability that the SINR of cellular user in a predefined interval, which constrains the corresponding transmission rate of cellular user. Secondly, in contrast to the previous studies with full traffic models, we employ queueing theory to evaluate the performance parameters of dynamic traffic model and formulate the cellular user transmission mechanism as a M/G/1 queuing model. In the derivation, Embedded Markov chain is introduced to depict the stationary distribution of cellular user queue status. Thirdly, the expressions of performance metrics in terms of mean queue length, mean throughput, mean delay and mean dropping probability are obtained, respectively. Simulation results show the validity and rationality of the theoretical analysis under different channel conditions.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1990년도 춘계공동학술대회논문집; 한국과학기술원; 28 Apr. 1990
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• pp.22-31
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• 1990

본 논문에서는 컴퓨터 통신 프로토콜의 모델링과 시뮬레이션에 관한 이론적 인 연구를 하였다. 먼저 통신 프로토콜의 정의와 기능을 설명하였고 통신 프 로토콜을 위한 모델을 분류하였다. 또한, 통신 프로토콜의 모델 중에 Timed Petri Net(TPN) 모델에 시간함수 .tau.를 부여함으로써 TPN을 구조적으로 정의하였으며 TPN Based 모델의 문제점을 보완하기 위하여 시스템 시뮬레 이션 분야의 이산사건 시스템 명세(DEVS:Discrete Event Simulation) 개념 을 도입하였다. 중요한 연구 결과로서 TPN모델이 DEVS모델이라는 정리를 제시하고 증명하였다. 이 정리에 따르면, TPN모델을 시뮬레이션 할 때 시뮬 레이션을 위해 모델을 설계할 필요없이 DEVS모델로 변환하여 사용함으로써 시뮬레이션을 수행할수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.