• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.98-107
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• 1996

In this paper, we propose a scheme that maps the time-delay neural network (TDNN) into the neurocomputer called EMIND-II which has the wavefront toroidal mesh-array structure. This neurocomputer is scalable, consists of many timeshared virtual neurons, is equipped with programmable on-chip learning, and is versatile for building many types of neural networks. Also we define the programming model of this array and derive the parallel algorithms about TDNN for the proposed neurocomputer EMIND-II. In addition, the computational complexities for the parallel and serial algorithms are compared. Finally, we introduce an application of this neurocomputer to word recognition.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.60-71
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• 2019

As IoT systems such as smart farms and smart cities become popular, a large amount of data collected from many sensor nodes is sent to a server in the Internet, which causes network traffic explosion, delay in delivery, and increase of server's workload. To solve these problems, the concept of fog computing has been proposed to store data between IoT systems and servers. In this study, we implemented a software platform of the fog node and applied it to the prototype smart farm system in order to check whether the problems listed above can be solved when using the fog node. When the fog node is used, the time taken to control an IoT device is lower than the response time of the existing IoT device-server case. We confirmed that it can also solve the problem of the Internet traffic explosion and the workload increase in the server. We also showed that the intelligent control of IoT system is feasible by having the data visualization in the server and real time remote control, emergency notification in the fog node as well as data storage which is the basic capability of the fog node.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.21-26
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• 2012

As the new requirements for wireless sensor networks are emerging, real-time communications is becoming a major research challenge because resource-constrained sensor nodes are not powerful enough to accommodate the complexity of the protocol. In addition, an efficient energy management scheme has naturally been a concern in wireless sensor networks for a long time. However, the existing schemes are limited to meeting one of these two requirements. To address the two factors together, we propose real-time communications with two approaches, a protocol for satisfied conditions and one for unsatisfied. Under the satisfied requirement, existing real-time protocol is employed. On the other hand, for the unsatisfied requirement, the newly developed scheme replaces the existing scheme by adjusting the transmission range of some surplus nodes. By expanding the transmission range, the end-to-end delay is shortened because the number of intermediate nodes decreases. These nodes conserve their energy for real-time communications by avoiding other activities such as sensing, forwarding, and computing. Finally, simulation results are given to demonstrate the feasibility of the proposed scheme in high traffic environments.

• Journal of the Korea Society of Computer and Information
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• v.17 no.5
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• pp.1-7
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• 2012

In this paper, we design and implement the simulator for WAN storage replication model performance evaluation in cloud computing environment. Each cloud of simulator is composed of virtual machine emulator and storage emulator. The virtual machine emulator is composed of read/write ratio module, the read/write sequence combination module, and the read/write request module. The storage emulator is composed of storage management module, data transfer module, read/write operations module, and overhead processing module. Using the simulator, we evaluate performance of migration scheme, pre-copy and the post-copy, considering about read/write ratio, network delay, and network bandwidth. Through simulation, we have confirmed that the average migration time of pre-copy was decreased proportional to the read operation. However, average migration time of post-copy was on the increase. Also, the average migration time of post-copy was increased proportional to the network delay. However, average migration time of pre-copy was shown uniformly. Therefore, we show that pre-copy model more effective to reduce the average migration time than the post-copy model. The average migration time of pre-copy and post-copy were not affected by the change of network bandwidth. Therefore, these results show that selects the storage replication model to be, the network bandwidth know not being the important element.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.47-58
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• 2009

Calibrating toll roads of highway networks needs additional weights within volume delay functions not like other general highway lints. However, current methods assigning additional weights in the volume delay function of toll roads are not sufficiently enough to predict real toll road volumes measured, since it does not consider discounting rates and an extra charges. This study develops methods to improve relevant and reliable volume delay functions. Suggested ideas include a method of weighting volume delay functions considering a value of time of vehicle types, a method of weighting volume delay functions considering lane distributions of vehicles, and a method of weighting volume delay functions considering percentages of link lengths per a number of lanes of toll roads. It is found that the method of weighting volume delay functions considering lane distributions of vehicles show most reliable and appropriate results, while the first method shows overestimation and the third method does underestimation of highway link volumes. In terms of assignment methods, total OD equilibrium assignment shows better results than PCU based assignment.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1029-1035
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• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• Smart Media Journal
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• v.8 no.3
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• pp.41-46
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• 2019

In a MMORPG, a typical application of virtual environment systems, it is a common desire to play in a more realistic environment. However, it is very difficult to provide a latency-free virtual environment to a large user base, mainly due to the fact that the real environment must be configured on multiple servers rather than on single server and that data must be shared on the real server when users move from one region to another. Experiencing response delays continuously in the process of information synchronization between servers greatly deteriorates the degree of immersion. In order to solve this problem, it is necessary to minimize the response delay occurring in the information synchronization process between the servers. In this paper, we propose Migration Agent for efficient information synchronization between field servers providing information of virtual environment and minimizing response delay between Field Server and PC(Player Character) and implement it in cloud computing network. In the proposed system, CPU utilization of field server increased by 6 ~ 13%, and response time decreased by 5 ~ 10 seconds over the existing system in 70,000 ~ 90,000 PCs

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.5
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• pp.312-325
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• 2006

Integration applications, such as EAI, B2Bi, need stable massive data processing systems during overload state cause by service request congestion in a short period time. In this paper, we propose the PLC (Peak Load Control)-based Worker-Linker pattern, which can effectively and stably process massive I/O transactions in spite of overload state generated by service request congestion. This pattern uses the delay time algorithm for the PLC mechanism. In this paper, we also show the example of applying the pattern to business-business integration framework and the experimental result for proving the stability of performance. According to our experiment result, the proposed delay time algorithm can stably control the heavy overload after the saturation point and has an effect on the controlling peak load.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.17-23
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• 2016

Wireless sensor-actuator networks (WSANs) enhance the existing wireless sensor networks (WSNs) by equipping sensor nodes with an actuator. The actuators work with the sensor nodes and perform application-specific operations. The WSAN systems have several applications such as disaster relief, intelligent building, military surveillance, health monitoring, and infrastructure security. These applications require capability of reliable data transfer to act responsively and accurately. Biologically inspired modeling techniques have received considerable attention for achieving robustness, scalability, and adaptability, while retaining individual simplicity. In this paper, an epidemic-inspired algorithm for data dissemination with delay constraints while minimizing energy consumption in WSAN is proposed. The steady states and system stability are analyzed using control theory. Also, simulation results indicate that the proposed scheme provides desirable dissemination delay and energy saving.