• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2253-2280
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• 2024

In the upcoming era of transportation, a groundbreaking technology, known as vehicle-to-everything (V2X) communication, is poised to redefine our driving experience and revolutionize traffic management. Real-time and secure communication plays a pivotal role in V2X networks, with the decision-making process being a key factor in establishing communication and determining malicious nodes. The proposed framework utilizes a directed acyclic graph (DAG) to facilitate real-time processing and expedite decision-making. This innovative approach ensures seamless connectivity among vehicles, the surrounding infrastructure, and various entities. To enhance communication efficiency, the entire roadside unit (RSU) region can be subdivided into various sub-regions, allowing RSUs to monitor and govern each sub-region. This strategic approach significantly reduces transaction approval time, thereby improving real-time communication. The framework incorporates a consensus mechanism to ensure robust security, even in the presence of malicious nodes. Recognizing the dynamic nature of V2X networks, the addition and removal of nodes are aligned. Communication latency is minimized through the deployment of computational resources near the data source and leveraging edge computing. This feature provides invaluable recommendations during critical situations that demand swift decision-making. The proposed architecture is further validated using the "veins" simulation tool. Simulation results demonstrate a remarkable success rate exceeding 95%, coupled with a significantly reduced consensus time compared to prevailing methodologies. This comprehensive approach not only addresses the evolving requirements of secure V2X communication but also substantiates practical success through simulation, laying the foundation for a transformative era in transportation.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.925-926
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• 2006

In the multi-agent system for a single task, the action selection can be made for the real-time environment by using the global coordination space, global coordination graph and MAX-PLUS algorithm. However, there are some difficulties in multi-agent system for multi-tasking. In this paper, a real-time decision making method is suggested by using coordination space, coordination graph and dynamic coordinated state of multi-agent system including many agents and multiple tasks. Specifically, we propose locally dynamic coordinated state to effectively use MAX-PLUS algorithm for multiple tasks completion. Our technique is shown to be valid in the box pushing simulation of a multi-agent system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.4
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• pp.287-295
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• 2022

As low altitude long-range artillery threat has been strengthened, the development of anti-artillery interception system to protect assets against its attacks will be kicked off. We view the defense of long-range artillery attacks as a typical dynamic weapon target assignment (DWTA) problem. DWTA is a sequential decision process in which decision making under future uncertain attacks affects the subsequent decision processes and its results. These are typical characteristics of Markov decision process (MDP) model. We formulate the problem as a MDP model to examine the assignment policy for the defender. The proximity of the capital of South Korea to North Korea border limits the computation time for its solution to a few second. Within the allowed time interval, it is impossible to compute the exact optimal solution. We apply approximate dynamic programming (ADP) approach to check if ADP approach solve the MDP model within processing time limit. We employ Shoot-Shoot-Look policy as a baseline strategy and compare it with ADP approach for three scenarios. Simulation results show that ADP approach provide better solution than the baseline strategy.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2200-2204
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• 2009

In this paper the analysis of natural cause of Beijing Storm inundation and the effect of the human activities has been taken. Flood risk can hardly be eliminated solely by projects. Pre-warning system established is an efficient measure to minimize the influence of flood. Several main functions of this system and their examples are described in the paper, such as: monitoring, forecast, scheme, warning, dynamic decision-making and information publication.

• Journal of the Korean Institute of Navigation
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• v.23 no.2
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• pp.11-22
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• 1999

This paper is concerned with the development of a tractable model to assist liner shipping companies in the decision-making of empty container repositioning and leasing. A hybrid methodology is presented which properly accounts for the specific characteristics of empty container management. For this mathematical models are developed based on dynamic network models, covering both land and marine segment. Then a stochastic method is presented to deal with the uncertainty of the future demand and supply. Especially, the concept of opportunity cost has been introduced in order to explain interactions between the variation of the future demand and supply and the stock level at each depot.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.73-79
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• 1994

This paper propose Adaptive Maintenance as a new type of maintenance for machine failures which are unpredictable. A purpose of adpative maintenance is to decrease inconsistency. In order to pick up some of problems the traditional maintenance policy, We discussed Time Based Maintenance(TBM) and Condition Based Maintenance(CBM) with Bath-Tub Curve. By using Machine Condition Diagnosis Technique (CDT), Monitored condition maintenance deals with the dynamic decision making for diagnosis procedures at maintenance and caution level. Adaptive Maintenance is a powerful tool for Total Production Maintenance(TPM).

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.4
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• pp.264-274
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• 2006

Recently, a variety of organizations including enterprises tend to try to use reporting tools as a data analysis tool for decision making support because reporting tools are capable of formatting data flexibly. Traditional reporting tools have thin-client structure in which all of dynamic documents are generated in the server side. This structure enables reporting tools to avoid repetitive process to generate dynamic documents, when many clients intend to access the same dynamic document. However, generating dynamic documents for data analysis doesn't consider a number of potential readers and increases requests to the server by making clients input various parameters at short intervals. In the structure of the traditional reporting tools, the increase of these requests leads to the increase of processing load in the server side. Thus, we present the reporting tool that can generate dynamic documents at the client side. This reporting tool has a processing mechanism to deal with a number of data despite the limited memory capacity of the client side.

• Journal of Korean Society of Forest Science
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• v.90 no.6
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• pp.725-733
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• 2001

In this study, the relationship between growth factors for Pinus densiflora stands in Anmyun-Island was analyzed and dynamic growth model was prepared. A total of 96 sample plots was investigated in which dbh and height of individual trees were measured. From these plot data, quadratic mean dbh, mean height, dominant tree height, stem number per ha, basal area per ha and volume per ha were estimated. Several regression equations between growth factors were derived using NLIN and REG procedure of SAS. And dynamic growth model, in which the equations were interactively linked, was prepared for the prediction of stand growth and yield under different management regime. The predictions of dynamic growth model were found to be coincided with general growth principles. The dynamic growth model was considered as adequate for predicting growth and yield of Pinus densiflora stand in Anmyun-Island. In practice, the dynamic growth model can be applied for predicting the growth and development of stand for various forest treatments and for decision-making in forest management.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1079-1085
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• 2000

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). An immune system is the living bodys self-protection and self-maintenance system. these features can be applied to decision making of the optimal swarm behavior in a dynamically changing environment. For applying immune system to DARS, a robot is regarded as a B-cell, each environmental condition as an antigen, a behavior strategy as an antibody, and control parameter as a T-cell, respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robots using communication (immune network). Finally, much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of the optimal swarm strategy. Adaptation ability of the robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5631-5652
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• 2019

The existing defense strategy selection methods based on game theory basically select the optimal defense strategy in the form of mixed strategy. However, it is hard for network managers to understand and implement the defense strategy in this way. To address this problem, we constructed the incomplete information stochastic game model for the dynamic analysis to predict multi-stage attack-defense process by combining Bayesian game theory and the Markov decision-making method. In addition, the payoffs are quantified from the impact value of attack-defense actions. Based on previous statements, we designed an optimal defense strategy selection method. The optimal defense strategy is selected, which regards defense effectiveness as the criterion. The proposed method is feasibly verified via a representative experiment. Compared to the classical strategy selection methods based on the game theory, the proposed method can select the optimal strategy of the multi-stage attack-defense process in the form of pure strategy, which has been proved more operable than the compared ones.