• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.163-171
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• 2021

In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.71-77
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• 2021

Recently, there is a demand for efficient program development of an IoT application support frameworks considering heterogeneous hardware characteristics. In addition, the scope of hardware support is expanding with the development of neuromorphic architecture that mimics the human brain to learn on their own and enables autonomous computing. However, most existing IoT IDE(Integrated Development Environment), it is difficult to support AI(Artificial Intelligence) or to support services combined with various hardware such as neuromorphic architectures. In this paper, we design an AI component abstract model that supports the second-generation ANN(Artificial Neural Network) and the third-generation SNN(Spiking Neural Network), and implemented an autonomous IoT IDE based on the proposed model. IoT developers can automatically create AI components through the proposed technique without knowledge of AI and SNN. The proposed technique is flexible in code conversion according to runtime, so development productivity is high. Through experimentation of the proposed method, it was confirmed that the conversion delay time due to the VCL(Virtual Component Layer) may occur, but the difference is not significant.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.269-276
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• 2021

Recently, smart sensors are used in various environments, and the implementation of ad-hoc sensor networks (ASNs) is a hot research topic. Unfortunately, traditional sensor network routing algorithms focus on specific control issues, and they can't be directly applied to the ASN operation. In this paper, we propose a new routing protocol by using the Q-learning technology, Main challenge of proposed approach is to extend the life of ASNs through efficient energy allocation while obtaining the balanced system performance. The proposed method enhances the Q-learning effect by considering various environmental factors. When a transmission fails, node penalty is accumulated to increase the successful communication probability. Especially, each node stores the Q value of the adjacent node in its own Q table. Every time a data transfer is executed, the Q values are updated and accumulated to learn to select the optimal routing route. Simulation results confirm that the proposed method can choose an energy-efficient routing path, and gets an excellent network performance compared with the existing ASN routing protocols.

• Cross-Cultural Studies
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• v.23
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• pp.243-264
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• 2011

The results of 2000 Population Census explains the context of a series of incidents happening in the Latino television broadcasting market recently. That is, the rapid growth of Latino population so fast as overtaking the Black population has needed media as a means of Latino's own social interests and communication. In this context, the television broadcasting market as a marketing means of capitals targeting for the Latinos has experienced more rapid changes. In other words, there has been some changes in the Latino television broadcasting market which divided by two major networks, Univision and Telemundo. It was 1970s when Latino media started to be considered as an important framework to understand the problems of the Latinos in American society. Experiencing the human rights movement of the 1960s, the Latino communities' sense of identity realized the importance of media as an expression of themselves from the interest on the factors which directly determine the quality of their life such as the immigration, education, health, and employment. The anglo media plays a role in introducing the Latinos and forming the images of the Latinos to the non-Latinos. It can be possible to criticize that the anglo media propagates the unilateral image of the Latinos by the mainstream white society, the stereotyped images of the Latinos. The spanish media targeting for the Latinos has grown continuously, combining the inside needs of forming the identity of the Latinos and communication and outside needs of commercialism. On the other hand, the needs for the programs based on the American Latinos has been increased, along with the increase of the Latino media based on the dual languages or English. This paper reviewed the history of the Latino media briefly, and then examined the relationship between the Latinos and the media through the television broadcasting which influence the Latino's everyday life enormously.

• Smart Media Journal
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• v.7 no.4
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• pp.52-60
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• 2018

Energy Management System(EMS) of Microgrid(MG) collects and analyzes data from devices in the microgrid to provide information to operators, users and other systems. In the middle of the process, it is required to securely provide information through both wired and wireless communication networks. In this paper, we design and implement a module that provides encryption and decryption, key management, key distribution, and message authentication functions, thus enabling the development of a system which is safe from the exposure and modulation of data potentially occurrable during data transmission between RTU(Remote Terminal Unit) and EMS. Our method can increase the efficiency of connection and key management for RTU by connecting a virtual device(VD) to RTU.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.123-128
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• 2018

Recently, the number of elderly people residing in nursing homes has increased rapidly due to the increase in the elderly population and the introduction of long-term care insurance. These long-term care patients suffer from chronic illnesses and dementia, and thus suffer from inconveniences or lack of cognitive ability. Thus, psychological and emotional support is urgent because they are depressed away from their families. Therefore, in this paper, we aim to provide a virtual experience of overseas trips by using VR and Photon networks for elderly patients with mobility difficulties. Existing VR-based travel experience service is doing alone, but the proposed contents can enjoy the scenery together with the view of the family member as well as the conversation during the travel experience. It is expected that the elderly patients with long - term care will be able to restore their psychological stability and improve their willingness to heal and improve their quality of life from the proposed application.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.121-126
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• 2018

IEEE 802.1 TSN TG is developing standards for end-to-end delay bounds and zero packet loss based on Ethernet technology. We focus on packet forwarding techniques. TSN packet forwarding techniques can be classified into Synchronous and Asynchronous framework. Synchronous approach allocates fixed time period for a class, yet is complex for large networks. Asynchronous approach provides delay guarantee by regulator-scheduler pair, yet is unnecessarily complex, too. We propose network components for TSN Asynchronous architecture, which remove the complexity of maintaining flow state for regulation decisions. Despite such a simplicity, the proposed architecture satisfies the TSN's delay requirements provided the limited high priority traffic's maximum packet length.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.27-33
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• 2019

The min-cut problem that decides the maximum flow in a complex network flows from source(s) to sink(t) is known as a hard problem. The augmenting path algorithm divides into single path and decides the bottleneck point(edge), but the min-cut section to be decide additionally. This paper suggests O(n) time complexity heuristic greedy algorithm for the number of vertices n that applies free agent system in a pro-sports field. The free agent method assumes $N_G(S),N_G(T)$vertices among $v{\in}V{\backslash}\{s,t\}$to free agent players, and this players transfer into the team that suggest more annual income. As a result of various networks, this algorithm can be finds all of min-cut sections and min-cut value for whole cases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.161-167
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• 2019

Recently, demand forecasting techniques have been actively studied due to interest in stable power supply with surging power demand, and increase in spread of smart meters that enable real-time power measurement. In this study, we proceeded the deep learning prediction model experiments which learns actual measured power usage data of home and outputs the forecasting result. And we proceeded pre-processing with moving average method. The predicted value made by the model is evaluated with the actual measured data. Through this forecasting, it is possible to lower the power supply reserve ratio and reduce the waste of the unused power. In this paper, we conducted experiments on three types of networks: Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short Term Memory (LSTM) and we evaluate the results of each scheme. Evaluation is conducted with following method: MSE(Mean Squared Error) method and MAE(Mean Absolute Error).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5179-5202
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• 2018

Transmission Control Protocol (TCP) is the most widely used protocol in the cloud data centers today. However, cloud data centers using TCP experience many issues as TCP was designed based on the assumption that it would primarily be used in Wide Area Networks (WANs). One of the major issues with TCP in the cloud data centers is the Incast issue. This issue arises because of the many-to-one communication pattern that commonly exists in the modern cloud data centers. In many-to-one communication pattern, multiple senders simultaneously send data to a single receiver. This causes packet loss at the switch buffer which results in TCP throughput collapse that leads to high Flow Completion Time (FCT). Recently, Software-Defined Networking (SDN) has been used by many researchers to mitigate the Incast issue. In this paper, a detailed survey of various SDN based solutions to the Incast issue is carried out. In this survey, various SDN based solutions are classified into four categories i.e. TCP Receive Window based solutions, Tuning TCP Parameters based solutions, Quick Recovery based solutions and Application Layer based solutions. All the solutions are critically evaluated in terms of their principles, advantages, and shortcomings. Another important feature of this survey is to compare various SDN based solutions with respect to different performance metrics e.g. maximum number of concurrent senders supported, calculation of delay at the controller etc. These performance metrics are important for deployment of any SDN based solution in modern cloud data centers. In addition, future research directions are also discussed in this survey that can be explored to design and develop better SDN based solutions to the Incast issue.