• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.5
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• pp.45-54
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• 1998

For proper release of side airbags, the onset of crash should be detected first. After crash detection, the algorithm has to make a decision whether the side airbag deployment is necessary. If the deployment is necessary, proper timing has to be provided for the maximum protection of driver or passenger. The side airbag release algorithm should be robust against the statistical deviations which are inherent to experimental crash test data. Deterministic optimization algorithms cannot be used for the side aribag release algorithm since the objective function cannot be expressed in a closed form. From this background, genetic algorithm has been used for the optimization. The optimization requires moderate amount of computation and gives satisfactory results.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1090-1100
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• 2021

Recently, as indoor activities increase due to the spread of infectious diseases, the metaverse is attracting attention. Metaverse refers to content in which the virtual world and the real world are closely related, and its representative platform technology is VR(Virtual Reality). However, since VR hardware is difficult to access in terms of cost, the concept of streaming-based cloud VR has emerged. This study proposes a server configuration and deployment method in an edge network when metaverse content involving multiple users operates based on cloud VR. The proposed algorithm deploys the edge server in consideration of the network and computing resources and client location for cloud VR, which requires a high level of computing resources while at the same time is very sensitive to latency. Based on simulation, it is confirmed that the proposed algorithm can effectively reduce the total network traffic load regardless of the number of applications or the number of users through comparison with the existing deployment method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.3030-3049
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• 2023

With the development and wide application of hybrid network computing modes like cloud computing, edge computing and fog computing, the customer service requests and the collaborative optimization of various computing resources face huge challenges. Considering the characteristics of network environment resources, the optimized deployment of service resources is a feasible solution. So, in this paper, the optimal goals for deploying service resources are customer experience and service cost. The focus is on the system impact of deploying services on load, fault tolerance, service cost, and quality of service (QoS). Therefore, the alternate node filtering algorithm (ANF) and the adjustment factor of cost matrix are proposed in this paper to enhance the system service performance without changing the minimum total service cost, and corresponding theoretical proof has been provided. In addition, for improving the fault tolerance of system, the alternate node preference factor and algorithm (ANP) are presented, which can effectively reduce the probability of data copy loss, based on which an improved cost-efficient replica deployment strategy named ICERD is given. Finally, by simulating the random occurrence of cloud node failures in the experiments and comparing the ICERD strategy with representative strategies, it has been validated that the ICERD strategy proposed in this paper not only effectively reduces customer access latency, meets customers' QoS requests, and improves system service quality, but also maintains the load balancing of the entire system, reduces service cost, enhances system fault tolerance, which further confirm the effectiveness and reliability of the ICERD strategy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1091-1110
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• 2016

Hybrid deployment under current cloud data centers is a combination of online and offline services, which improves the utilization of the cluster resources. However, the performance of the cluster is often affected by the online services in the hybrid deployment environment. To improve the response time of online service (e.g. search engine), an effective scheduling algorithm based on Storm is proposed. At the component level, the algorithm dispatches the component with more influence to the optimal performance node. Inside the component, a reasonable resource allocation strategy is used. By searching the compressed index first and then filtering the complete index, the execution speed of the component is improved with similar accuracy. Experiments show that our algorithm can guarantee search accuracy of 95.94%, while increasing the response speed by 68.03%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.277-290
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• 2019

The demand for indoor positioning is increasing day by day. However, the widely used positioning methods today cannot satisfy the requirements of the indoor environment in terms of the positioning accuracy and deployment cost. In the existing research domain, the localization algorithm based on three-dimensional space is less accurate, and its robustness is not high. Visible light communication technology (VLC) combines lighting and positioning to reduce the cost of equipment deployment and improve the positioning accuracy. Further, it has become a popular research topic for telecommunication and positioning in the indoor environment. This paper proposes a surface centroid TOA localization algorithm based on the VLC system. The algorithm uses the multiple solutions estimated by the trilateration method to form the intersecting planes of the spheres. Then, it centers the centroid of the surface area as the position of the unknown node. Simulation results show that compared with the traditional TOA positioning algorithm, the average positioning error of the surface centroid TOA algorithm is reduced by 0.3243 cm and the positioning accuracy is improved by 45%. Therefore, the proposed algorithm has better positioning accuracy than the traditional TOA positioning algorithm, and has certain application value.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.32-38
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• 2020

The deployment of geographically distributed wireless sensors has greatly elevated the capability of monitoring structural health in social-overhead capital (SOC) public infrastructures. This paper deals with the utilization of a distributed mobility management (DMM) approach for the deployment of wireless sensing devices in a structural health monitoring system (SHM). Then, a wireless sensing mechanism utilizing low-energy adaptive clustering hierarchy (LEACH)-based clustering algorithm for smart sensors has been analyzed to support the seamless data transmission of structural health information which is essentially important to guarantee public safety. The clustering of smart sensors will be able to provide real-time monitoring of structural health and a filtering algorithm to boost the transmission of critical information over heterogeneous wireless and mobile networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1084-1090
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• 2015

In this paper, we propose a Tabu search algorithm to efficiently deploy the sensor nodes for maximizing the network sensing coverage in wireless sensor networks. As the number of the sensor nodes in wireless sensor networks increases, the amount of calculation for searching the solution would be too much increased. To obtain the best solution within a reasonable execution time in a high-density network, we propose a Tabu search algorithm to maximize the network sensing coverage. In order to search effectively, we propose some efficient neighborhood generating operations of the Tabu search algorithm. We evaluate those performances through some experiments in terms of the maximum network sensing coverage and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.31-39
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• 2011

For rapid formed the ad hoc wireless backbone network in disaster scene, It is necessary for real-time deployment scheme of wireless ad hoc relay devices by first responders without pre-planning. However, in order to realize this scheme, redundant deployment should be minimized, as well as optimal location of relay devices should be selected to expand communication coverage. Therefore, in this paper, we propose a new deployment scheme of relay devices to optimize communication coverage and then through simulations showed that improved performance of algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.4
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• pp.193-203
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• 2001

The Monte Carlo method was used to evaluate the reliability of crash discrimination algorithms. Through the Fast Fourier Transformation, crash pulses obtained during frontal crash tests of a mini van and a sports utility vehicle were transformed to signals in the frequency domain, and the signals were divided into basic signals and changeable signals. The changeable signals were modified through random generation, and they were combined with the basic signals. Then, the combined signals were transferred back to the time domain. In this way numerous crash pulses could be generated. For the generated pulses, crash discrimination algorithms were evaluated by examining whether they did not result in air bag deployment for the pulses requiring no air bag deployment and whether they resulted in time-to-fires faster than required time-to-fires for the pulses requiring air bag deployment. The crash discrimination algorithm in which the absolute value of the deceleration change multiplied by the velocity change or the summation of the absolute value of the deceleration change was used as a metric was Proven to be highly reliable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1501-1518
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• 2016

This paper presents an effective management of VM (Virtual Machine) for heterogeneous cloud using Common Deployment Model (CDM) brokering mechanism. The effective utilization of VM is achieved by means of task scheduling with VM placement technique. The placements of VM for the physical machine are analyzed with respect to execution time of the task. The idle time of the VMis utilized productively in order to improve the performance. The VMs are also scheduled to maintain the state of the current VM after the task completion. CDM based algorithm maintains two directories namely Active Directory (AD) and Passive Directory (PD). These directories maintain VM with proper configuration mapping of the physical machines to perform two operations namely VM migration and VM roll back. VM migration operation is performed from AD to PD whereas VM roll back operation is performed from PD to AD. The main objectives of the proposed algorithm is to manage the VM's idle time effectively and to maximize the utilization of resources at the data center. The VM placement and VM scheduling algorithms are analyzed in various dimensions of the cloud and the results are compared with iCanCloud model.