• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.162-169
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• 2022

In a dynamically changing time-varying network environment, the optimal moving pattern of edge devices can be applied to distributing computing resources to edge cloud servers or deploying new edge servers in the FEC(Fog/Edge Computing) environment. In addition, this can be used to build an environment capable of efficient computation offloading to alleviate latency problems, which are disadvantages of cloud computing. This paper proposes an algorithm to extract the optimal moving pattern by analyzing the moving path of multiple edge devices requiring application services in an arbitrary spatio-temporal environment based on frequency. A comparative experiment with A^* and Dijkstra algorithms shows that the proposed algorithm uses a relatively fast execution time and less memory, and extracts a more accurate optimal path. Furthermore, it was deduced from the comparison result with the A^* algorithm that applying weights (preference, congestion, etc.) simultaneously with frequency can increase path extraction accuracy.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.152-163
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• 2022

In this paper, we present a method to enable an unmanned aerial vehicle to drop the sonobuoy, an essential element of anti-submarine warfare, in an optimal deployment. To this end, an environment simulating the distribution of sound detection performance was configured through the Unity game engine, and the environment directly configured using Unity ML-Agents and the reinforcement learning algorithm written in Python from the outside communicated with each other and learned. In particular, reinforcement learning is introduced to prevent the accumulation of wrong actions and affect learning, and to secure the maximum detection area for the sonobuoy while the vehicle flies to the target point in the shortest time. The optimal placement of the sonobuoy was achieved by applying the Deep Deterministic Policy Gradient (DDPG) algorithm. As a result of the learning, the agent flew through the sea area and passed only the points to achieve the optimal placement among the 70 target candidates. This means that an autonomous aerial vehicle that deploys a sonobuoy in the shortest time and maximum detection area, which is the requirement for optimal placement, has been implemented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.159-160
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• 2013

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3474-3497
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• 2016

Network Function Virtualization (NFV) and Software Defined Networking (SDN) are recently considered as very promising drivers of the evolution of existing middlebox services, which play intrinsic and fundamental roles in today's networks. To address the virtual service deployment issues that caused by introducing NFV or SDN to networks, this paper proposes an optimal solution by combining quantum genetic algorithm with cooperative game theory. Specifically, we first state the concrete content of the service deployment problem and describe the system framework based on the architecture of SDN. Second, for the service location placement sub-problem, an integer linear programming model is built, which aims at minimizing the network transport delay by selecting suitable service locations, and then a heuristic solution is designed based on the improved quantum genetic algorithm. Third, for the service amount placement sub-problem, we apply the rigorous cooperative game-theoretic approach to build the mathematical model, and implement a distributed algorithm corresponding to Nash bargaining solution. Finally, experimental results show that our proposed method can calculate automatically the optimized placement locations, which reduces 30% of the average traffic delay compared to that of the random placement scheme. Meanwhile, the service amount placement approach can achieve the performance that the average metric values of satisfaction degree and fairness index reach above 90%. And evaluation results demonstrate that our proposed mechanism has a comprehensive advantage for network application.

• Smart Structures and Systems
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• v.21 no.4
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• pp.407-420
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• 2018

In structural health monitoring, it is meaningful to comprehensively utilize accelerometers and strain gauges to obtain the modal information of a structure. In this paper, a modal estimation theory is proposed, in which the displacement modes of the locations without accelerometers can be estimated by the strain modes of selected strain gauge measurements. A two-stage sensor placement method, in which strain gauges are placed together with triaxial accelerometers to obtain more structural displacement mode information, is proposed. In stage one, the initial accelerometer locations are determined through the combined use of the modal assurance criterion and the redundancy information. Due to various practical factors, however, accelerometers cannot be placed at some of the initial accelerometer locations; the displacement mode information of these locations are still in need and the locations without accelerometers are defined as estimated locations. In stage two, the displacement modes of the estimated locations are estimated based on the strain modes of the strain gauge locations, and the quality of the estimation is seen as a criterion to guide the selection of the strain gauge locations. Instead of simply placing a strain gauge at the midpoint of each beam element, the influence of different candidate strain gauge positions on the estimation of displacement modes is also studied. Finally, the modal assurance criterion is utilized to evaluate the performance of the obtained multitype sensor placement. A bridge benchmark structure is used for a numerical investigation to demonstrate the effectiveness of the proposed multitype sensor placement method.

• Journal of Aerospace System Engineering
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• v.18 no.3
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• pp.1-7
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• 2024

The utilization of Unmanned Aerial Vehicles (UAVs) is expanding in various industries such as logistics, manufacturing, and transportation. However, to operate a large number of UAVs, it is imperative to first plan a secure and efficient self-configuring communication network for UAVs. In this study, we proposed a method for planning a secure and efficient UAV self-configuring communication network using Voronoi diagrams in the following three steps: 1) generating Voronoi diagrams using obstacles, 2) selecting obstacles to consider for path generation, and 3) planning the optimal path and outputting the path. The real-time feasibility of using the proposed method for planning optimal communication paths for a realistic number of UAVs was experimentally validated.

• Journal of Navigation and Port Research
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• v.37 no.1
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• pp.35-40
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• 2013

In the eLoran navigation system, the dominant deterioration factors of navigation accuracy are the TOA measurement errors on user receiver and the GDOP between the receiver and the transmitters. But if the ASF data measured at dLoran reference station are provided for users through the Loran data channel, it will be possible to correct the TOA measurement errors. The position accuracy can be determined by the DOP depending on the geometry of receiver-transmitters, and their optimal placement improves the navigation accuracy. In this study we determined the geometric placement in case of up to six stations, and evaluated the performance of position accuracy for the receiver-transmitter geometry set of eLoran stations. The proposed geometry of eLoran stations can be referred for the construction of eLoran infrastructure meeting the capability of HEA for maritime, and time/frequency users in Korea.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.202-207
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• 2016

Checkpoint placement is an effective fault tolerance technique against transient faults in which the task is re-executed from the latest checkpoint when a fault is detected. In this paper, we propose a new checkpoint placement strategy separating data saving and fault detection processes that are performed together in conventional checkpoints. Several fault detection processes are performed in one checkpoint interval in order to decrease the latency between the occurrence and detection of faults. We address the placement method of fault detection processes to maximize the probability of successful execution of a task within the given deadline. We develop the Markov chain model for a real-time task having the proposed checkpoints, and derive the optimal fault detection and checkpoint interval.

• Journal of the Korean Institute of Gas
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• v.20 no.2
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• pp.66-71
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• 2016

Nowadays, a number of sensors which are placed in industrial complex are monitoring areas involving chemical leak and other faults. However, even in the presence of the sensors, chemical leaks, sometimes involving huge amount of chemicals, continuously led to big losses in the industrial complex. In most industries, sensor installation has been performed using past experience or using senor manufacturers' guideline; which leads to poor performance of the installed sensor grid. Therefore, we investigate an optimal placement methodology of point sensors for rapid detention and response when chemical leaks happen. This research suggests a generalized formulation suitable for the optimized decision making of minimizing number of sensors to be placed and increasing the fraction of covered scenarios under assumption of negligible effect of other structures. The proposed method has been verified for suitable performance for simple leak scenario simulations, by achieving the safety objectives and guaranteeing safe process operations.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1373-1392
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• 2015

Placing sensors at appropriate locations is an important task in the design of an efficient structural health monitoring (SHM) system for a large-scale civil structure. In this paper, a hybrid optimization algorithm called virus monkey algorithm (VMA) based on the virus theory of evolution is proposed to seek the optimal placement of sensors. Firstly, the dual-structure coding method is adopted instead of binary coding method to code the solution. Then, the VMA is designed to incorporate two populations, a monkey population and a virus population, enabling the horizontal propagation between the monkey and virus individuals and the vertical inheritance of monkey's position information from the previous to following position. Correspondingly, the monkey population in this paper is divided into the superior and inferior monkey populations, and the virus population is divided into the serious and slight virus populations. The serious virus is used to infect the inferior monkey to make it escape from the local optima, while the slight virus is adopted to infect the superior monkey to let it find a better result in the nearby area. This kind of novel virus infection operator enables the coevolution of monkey and virus populations. Finally, the effectiveness of the proposed VMA is demonstrated by designing the sensor network of the Canton Tower, the tallest TV Tower in China. Results show that innovations in the VMA proposed in this paper can improve the convergence of algorithm compared with the original monkey algorithm (MA).