• Journal of Information Processing Systems
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• v.17 no.3
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• pp.489-504
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• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_3
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• pp.1135-1145
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• 2022

Due to increase in concerns related to the climate change, state-wide promotion of the carbon neutrality has been in progress thus far. Smart City could be one of the measures as the initiative to mitigate the missions process. The primary purpose of Smart City can be summarized to be maximization of the social net-beneift to be returned for the local citizens and derivation of the optimal pattern of the energy consumption could belong to one of the elements included in the net-benefit. Currently, the energy consumption by the buildings has been determined to be responsible for the greatest consumption among the sectors considered to be energy-intensive. Moreover, considering the fact that the consumption by operations of HVAC is responsible for nearly 40% in the commercial buildings, it is virtually not possible to optimize schedules for the energy consumption with considerable deliverables from the perspective of the urban planners. Thus, the methods to implement the optimal schedules for the HVAC commissioned with the OHUs were concluded to be the suitable candidate resources for the simulation by EnergyPlus capable of monitoring the thermal changes in each subject space in the present research.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.6
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• pp.503-512
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• 2018

SAR(Synthetic Aperture Radar) is a technology to acquire images by processing signals obtained from radar, and there is an increasing demand for utilization of high-resolution SAR images. In this paper, for high-speed processing of high-resolution SAR image data, a study for SAR image processing algorithms to achieve optimal performance in multi-core based computer architecture is performed. The performance deterioration due to a large amount of input/output data for high resolution images is reduced by maximizing the memory utilization, and the parallelization ratio of the code is increased by using dynamic scheduling and nested parallelism of OpenMP. As a result, not only the total computation time is reduced, but also the upper bound of parallel performance is increased and the actual parallel performance on a multi-core system with 10 cores is improved by more than 8 times. The result of this study is expected to be used effectively in the development of high-resolution SAR image processing software for multi-core systems with large memory.

• Journal of Astronomy and Space Sciences
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• v.23 no.3
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• pp.245-258
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• 2006

In this paper, an automation algorithm of analyzing and scheduling the station-keeping maneuver is presented for Communication, Ocean and Meteorological Satellite (COMS). The perturbation analysis for keeping the position of the geostationary satellite is performed by analytic methods. The east/west and north/south station-keeping maneuvers we simulated for COMS. Weekly east/west and biweekly north/south station-keeping maneuvers are investigated for a period of one year. Various station-keeping orbital parameters are analyzed. As the position of COMS is not yet decided at either $128.2^{\circ}E\;or\;116.0^{\circ}E$, both cases are simulated. For the case of $128.2^{\circ}E$, east/west station-keeping requires ${\Delta}V$ of 3.50m/s and north/south station-keeping requires ${\Delta}V$ of 52.71m/s for the year 2009. For the case of $116.0^{\circ}E,\;{\Delta}V$ of 3.86m/s and ${\Delta}V$ of 52.71m/s are required for east/west and north/south station-keeping, respectively. The results show that the station-keeping maneuver of COMS is more effective at $128.2^{\circ}E$.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1021-1028
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• 2005

The general solution for classification and regression problems can be found by matching and modifying matrices with the information in real world and then these matrices are teaming in neural networks. This paper treats primary space as a real world, and dual space that Primary space matches matrices using kernel. In practical study, there are two kinds of problems, complete system which can get an answer using inverse matrix and ill-posed system or singular system which cannot get an answer directly from inverse of the given matrix. Further more the problems are often given by the latter condition; therefore, it is necessary to find regularization parameter to change ill-posed or singular problems into complete system. This paper compares each performance under both classification and regression problems among GCV, L-Curve, which are well known for getting regularization parameter, and kernel methods. Both GCV and L-Curve have excellent performance to get regularization parameters, and the performances are similar although they show little bit different results from the different condition of problems. However, these methods are two-step solution because both have to calculate the regularization parameters to solve given problems, and then those problems can be applied to other solving methods. Compared with UV and L-Curve, kernel methods are one-step solution which is simultaneously teaming a regularization parameter within the teaming process of pattern weights. This paper also suggests dynamic momentum which is leaning under the limited proportional condition between learning epoch and the performance of given problems to increase performance and precision for regularization. Finally, this paper shows the results that suggested solution can get better or equivalent results compared with GCV and L-Curve through the experiments using Iris data which are used to consider standard data in classification, Gaussian data which are typical data for singular system, and Shaw data which is an one-dimension image restoration problems.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2484-2496
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• 2000

High speed switches have been developing to interconnect a large number of nodes. It is important to analyze the switch performance under various conditions to satisfy the requirements. Queueing analysis, in general, has the intrinsic problem of large state space dimension and complex computation. In fact, The petri net is a graphical and mathematical model. It is suitable for various applications, in particular, manufacturing systems. It can deal with parallelism, concurrence, deadlock avoidance, and asynchronism. Currently it has been applied to the performance of computer networks and protocol verifications. This paper presents a framework for modeling and analyzing ATM switch using stochastic activity networks (SANs). In this paper, we provide the ATM switch model using SANs to extend easily and an approximate analysis method to apply A TM switch models, which significantly reduce the complexity of the model solution. Cell arrival process in output-buffered Queueing A TM switch with finite buffer is modeled as Markov Modulated Poisson Process (MMPP), which is able to accurately represent real traffic and capture the characteristics of bursty traffic. We analyze the performance of the switch in terms of cell-loss ratio (CLR), mean Queue length and mean delay time. We show that the SAN model is very useful in A TM switch model in that the gates have the capability of implementing of scheduling algorithm.

• Journal of IKEEE
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• v.11 no.4
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• pp.348-357
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• 2007

Due to the improved performance and cost of personal mobile devices and rapid progress of wireless communication technology, the number of users who utilize these devices is increasing. This trend requires various types of services be available to users. So far, there have been many solutions provided for the shortest path problem. But, technologies which can offer various recommendation services to user depending on user’s current location are focused on Euclidean spaces rather than road network. Thus, in this paper, we extend the previous work to satisfy this requirement on road network database. Our proposed scheme requires pre-computation for the efficient query processing. In the preprocessing step, we first partition the input road network into a fixed number of Voronoi polygons and then pre-compute routing information for each polygon. In the meantime, we select the number of Voronoi polygons in proposition to the scale of road network. Through this selection, the required size of pre-computation is linearly increasing to the size of road network. Using this pre-computated information, we can process queries more quickly. Through experiments, we have shown that our proposed scheme can achieve excellent performance in terms of scheduling time and the number of visited nodes.

• Korean Journal of Construction Engineering and Management
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• v.14 no.5
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• pp.175-187
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• 2013

Each participant in building construction project requires their own workspace to execute their activities. In this environment, inappropriate workspace planning in construction site causes workspace conflicts which result in a loss of productivity, safety hazard and poor-quality issues. Therefore, workspace should be regarded as one of the most important resources and constraints have to be managed at construction site. However, current construction planning techniques such as Gantt chart, network diagram and critical path method have proven to be insufficient to workspace planning. This paper contains formalized process for workspace planning in 4D BIM environment to prevent workspace related problems in construction project. The proposed process in this paper represents workspace occupation status for each activity and suitable solutions for identified workspace conflicts by integrating workspace attributes and activity execution plan. Based on the result of this study, project manager will be able to prevent probable workspace conflicts and negative effect on project performance by devising appropriate workspace plan during preconstruction phase.

• Journal of IKEEE
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• v.5 no.1 s.8
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• pp.100-110
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• 2001

In this paper, we investigated several buffer management schemes for the design of shared-memory type ATM switches, which can enhance the utilization of switch resources and can support quality-of-service (QoS) functionalities. Our results show that dynamic threshold (DT) scheme demonstrate a moderate degree of robustness close to pushout(PO) scheme, which is known to be impractical in the perspective of hardware implementation, under various traffic conditions such as traffic loads, burstyness of incoming traffic, and load non-uniformity across output ports. Next, we considered buffer management strategies to support QoS functions, which utilize parameter values obtained via connection admission control (CAC) procedures to set tile threshold values. Through simulations, we showed that the buffer management schemes adopted behave well in the sense that they can protect regulated traffic from unregulated cell traffic in allocating buffer space. In particular, it was observed that dynamic partitioning is superior in terms of QoS support than virtual partitioning.

• The KIPS Transactions:PartC
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• v.16C no.1
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• pp.51-56
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• 2009

Time synchronization algorithm in wireless sensor networks is essential to various applications such as object tracking, data encryption, duplicate detection, and precise TDMA scheduling. This paper describes CDRS that is a time synchronization algorithm using the Clock Drift rate and Reference Signals between two sensor nodes. CDRS is composed of two steps. At first step, the time correction is calculated using offset and the clock drift rate between the two nodes based on the LTS method. Two nodes become a synchronized state and the time variance can be compensated by the clock drift rate. At second step, the synchronization node transmits reference signals periodically. This reference signals are used to calculate the time difference between nodes. When this value exceeds the maximum error tolerance, the first step is performed again for resynchronization. The simulation results on the performance analysis show that the time accuracy of the proposed algorithm is improved, and the energy consumption is reduced 2.5 times compared to the time synchronization algorithm with only LTS, because CDRS reduces the number of message about 50% compared to LTS and reference signals do not use the data space for timestamp.