• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3557-3566
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• 2015

In the case of elevated railway station in which railway is connected with superstructure of station, vibration and noise level is relatively higher than those of general structure type station due to structural characteristic which transmits vibration directly. Therefore, characteristic understanding of structural vibration and accompanying structure cause noise and establishment of reduction plan through the results are in need. Test and analysis are performed in this research to consider correlativity between structural vibration and accompanying structure cause noise when external forces are applied on standard slab and floating slab which is able to isolate vibration. By producing and loading on standard and floating slab, vibration and noise response are measured while simulation using numerical analysis, finite element method and SEA method is performed. The results about structural dynamic behavior of slab, correlativity between structural vibration and noise, reduction performance of floating slab is deduced through the analysis of tests.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6260-6268
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• 2015

In LTE-Advanced that different networks coexist, it is considered that it is actually difficult to provide service continuity with a procedural and static control method applied to the existing voice service. This paper suggests Service Self-Organization to support the service continuity effectively based on SON. It means a method in which a subscriber's terminal collects information about its current condition and base station around, and a base station, through the data collected by monitoring inner or adjacent base station, shares related data and converges, controlling service continuity on its own. In other words, as context information of mobile terminal and base station changes, set-up of related functions such as ISHO, cell selection, source allocation, load control, and QoS mapping is adapted; each function fits into the change, exchanges the process of reorganization, and interacts; these actions go toward to satisfy service continuity. Simulation results show that it provides better performances than the conventional one with the measure of resource utilization rate and outage probability.

• The KIPS Transactions:PartA
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• v.12A no.4 s.94
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• pp.273-280
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• 2005

The mobility or highly interconnected and communicating devices and users has implications for the QoS in a ubiquitous computing environment. Therefore, it is important for location aware systems to detect location of mobile object correctly and Provide high quality services in ubiquitous environment. However, it is not easy that location aware systems offer highly reliable QoS to users because process strategies of location aware systems are limited by the capability according to the applied detection target objects. In this paper, we design an autonomic architecture which analyzes the location aware system condition and autonomously chooses the best appropriate process strategy. We also have simulated the Proposed architecture in order to verify its performance. The test results show us that the architecture using self-optimizing mechanism provides higher QoS to users in variable bandwidth.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.4
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• pp.291-299
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• 2007

To operate a permanent magnet synchronous motor (PMSM) at a maximum torque per ampere (MTPA) operation point, the exact values of machine parameters such as inductances and back-EMF constant, which are sensitive to motor phase currents and temperature respectively, should be blown. An adaptive estimation method for on-line estimation of the machine parameters is not suitable for practical applications since it has difficulties in estimating exact values and requires complex mathematical calculations. The purpose of this paper is to present a simple MTPA operation point tracking control strategy for vector controlled PMSM drives with slow dynamic loads. The proposed method searches MTPA operation points by modulating current phase angle and observing the variation in command power. The current angle modulation strategy is designed to sense the effect of load variations in the command power. Therefore, the proposed method can track the MTPA operation points of the PMSM regardless of load variations. Computer simulation and experimental study is also presented to show the effectiveness of the proposed method.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.783-788
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• 2002

Adaptive Cyclic Packet Dropping algorithm (ACPD), and Non-adaptive Cyclic Packet Dropping algorithm (NCPD) are applying stricter drop precedence than that of RIO algorithm. Especially, the ACPD algorithm drops adaptively packets for the congestion control, as predicting traffic pattern between each cycle. Therefore the ACPD algorithm makes up for the drawback of RIO algorithm and minimizes the wastes of the bandwidth being capable of predicting in the NCPD algorithm. And we executed a simulation and analyzed the throughput and packet drop rate based on Sending Priority changing dynamically depending on network traffic. In this algorithm, applying strict drop precedence policy, we get better performance on priority levels. The results show that the proposed algorithms may provide more efficient and stricter drop precedence policy as compared to RIO independent of traffic load. The ACPD algorithm can provide better performance on priority levels and keep stricter drop policy than RIO and the NCPD algorithm.

• The KIPS Transactions:PartA
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• v.9A no.1
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• pp.9-18
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• 2002

In this paper, we propose scalable scheduling techniques based on EDF to efficiently integrate hard real-time and multimedia soft real-time tasks in the distributed real-time multimedia database system. Hard tasks are guarangteed based on worst case execution times, whereas multimedia soft tasks are served based on mean execution times. This paper describes a served-based scheme for partitioning the CPU bandwidth among different task classes that coexist in the same system. To handle the problem of class overloads characterized by varying number of tasks and varying task arrival rates, thus scheme shows how to adjust the fraction of the CPU bandwidth assigned to each class. This scheme fixes the maximum time that each hard task can execute in the period of the server, whereas it can dynamically change the bandwidth reserved to each multimedia task. The proposed method is capable of minimizing the mean tardiness of multimedia tasks, without jeopardizing the schedulability of the hard tasks. The performance of this scheduling method is compared with that of similar mechanisms through simulation experiments.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.9-18
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• 2014

The sensors attached on/in a person are moved since human body frequency changes their activity, therefore in wireless body area networks, nodal mobility and non-line-of-sight condition will impact on performance of networks such as energy efficiency and reliable communication. We then proposed schemes which study on forwarding decisions against frequent change of topology and channel conditions to increase reliable connections and improve energy efficiency. In this work, we control the size of packets, forwarding rate based on ratio of input links and output links at each node. We also robust the network topology by extending the peer to peer IEEE 802.15.4-based. The adaptive topology from chain-based to grid-based can optimal our schemes. The simulation shows that these approaches are not only extending network lifetime to 48.2 percent but also increase around 6.08 percent the packet delivery ratio. The "hot spots" problem is also resolved with this approach.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.39-47
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• 2020

This paper introduces a novel system-level framework that derives energy efficient electric vehicle (EV) driving speed profile to extend EV driving range without additional cost. This paper first implements an EV power train model considering forces acting on a driving vehicle and motor efficiency. Then, it derivate the minimum-energy driving speed profile for a given driving mission defined by the route. This framework first formulates an optimization problem and uses the dynamic programming algorithm with a weighting factor to derive a speed profile minimizing both of energy consumption and driving time. This paper introduces various weighting factor tracking methods to satisfy the driving time constraint. Simulation results show that runtime of the proposed scaling algorithm is 34% and 50% smaller than those of the binary search algorithm and greedy algorithm, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.587-595
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• 2015

Several fields of science have traditionally demanded large-scale workflow support, which requires thousands of central processing unit (CPU) cores. In order to support such large-scale scientific workflows, large-capacity cluster systems such as supercomputers are widely used. However, as users require a diversity of software packages and configurations, a system administrator has some trouble in making a service environment in real time. In this paper, we present a container-based cluster management platform and introduce an implementation case to minimize performance reduction and dynamically provide a distributed computing environment desired by users. This paper offers the following contributions. First, a container-based virtualization technology is assimilated with a resource and job management system to expand applicability to support large-scale scientific workflows. Second, an implementation case in which docker and HTCondor are interlocked is introduced. Lastly, docker and native performance comparison results using two widely known benchmark tools and Monte-Carlo simulation implemented using various programming languages are presented.