• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2405-2411
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• 2009

MMSE, ZF and ML are the decoding mechanisms for V-BLAST system, and ML shows the best performance decoding the original signal among them. However, it has a problem that the computation complexity is increased exponentially according to the number of transmit antennas and transmit degrees. In this paper, we propose a low complexity linear ML detection algorithm having low computation complexity, then analyze the system performance in BER and computation complexity comparing with other algorithms. In the simulation, the BER performance of the proposed algorithm is superior than ZF and MMSE detection algorithms, and similar to ML detection algorithm. However, its computation complexity was 50% less than ML algorithm. From the results, we confirm that the proposed algorithm is superior than other ML detection algorithms.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1329-1336
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• 1996

In many image compression applications, the discrete cosine transform (DCY) is well known for is highly efficient coding performance. However, it produces undesirable block artifacts in low-bit rate coding. In addition, in many practical applications, faster computation and easier VLST implementation of DCT coefficients are also important issues. The removal of the block artifacts and faster DCT computation are therefor of practical interest. In this paper, a modified DCTcomputation scheme was investigated, which provides a simple efficient solution to the reduction of the block artifacts while achieving faster computation. We have applied the new ap-proach to the low-bit rate coding and decoding of images. Simulation results on real images have verified the improved performance of the proposed method over the standar d method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4849-4864
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• 2019

Modern applications such as augmented reality, connected vehicles, video streaming and gaming have stringent requirements on latency, bandwidth and computation resources. The explosion in data generation by mobile devices has further exacerbated the situation. Mobile Edge Computing (MEC) is a recent addition to the edge computing paradigm that amalgamates the cloud computing capabilities with cellular communications. The concept of MEC is to relocate the cloud capabilities to the edge of the network for yielding ultra-low latency, high computation, high bandwidth, low burden on the core network, enhanced quality of experience (QoE), and efficient resource utilization. In this paper, we provide a comprehensive overview on different traits of MEC including its use cases, architecture, computation offloading, security, economic aspects, research challenges, and potential future directions.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.863-866
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• 2005

Low-power design is one of the most important challenges encountered in maximizing battery life in portable devices as well as saving energy during system operation. In this paper we propose a low-power DCT (Discrete Cosine Transform) architecture using a modified Computation Sharing Multiplication (CSHM). The overall rate of power consume is reduced during DCT: the proposed architecture does not perform arithmetic operations on unnecessary bits during the Computation Sharing Multiplication calculations. Experimental results show that it is possible to reduce power dissipation up to about $7{\sim}8%$ without compromising the final DCT results. The proposed lowpower DCT architecture can be applied to consumer electronics as well as portable multimedia systems requiring high throughput and low-power.

• Journal of Power Electronics
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• v.19 no.2
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• pp.529-539
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• 2019

The modular multilevel converter (MMC) has become a promising topology for high-voltage direct current (HVDC) transmission systems. To control a MMC system properly, the ac-side current, circulating current and submodule (SM) capacitor voltage are taken into consideration. This paper proposes a low-computation indirect model predictive control (IMPC) strategy that takes advantages of the conventional MPC and has no weighting factors. The cost function and duty cycle are introduced to minimize the tracking error of the ac-side current and to eliminate the circulating current. An optimized merge sort (OMS) algorithm is applied to keep the SM capacitor voltages balanced. The proposed IMPC strategy effectively reduces the controller complexity and computational burden. In this paper, a discrete-time mathematical model of a MMC system is developed and the duty ratio of switching state is designed. In addition, a simulation of an eleven-level MMC system based on MATLAB/Simulink and a five-level experimental setup are built to evaluate the feasibility and performance of the proposed low-computation IMPC strategy.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.639-642
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• 2005

Motion Estimation(ME) is an important part of video compression, because it requires a large amount of computation. Half-pixel and quarter-pixel motion estimation allows high video compression rates but it also has high computation complexity. In this paper we suggest a new and efficient motion estimation algorithm for half-pixel and quarter-pixel motion estimation using SAD values. In the method, an integer-pixel motion vector is found and then only three neighboring points of the integer-pixel motion vector is evaluated to find the half-pixel motion vector. The quarter-pixel motion vector is also found by using a similar method. Experimental results of our method shows 20% reduction in computation time, when compared with those of a conventional method, while producing same quality motion vectors.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.597-598
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• 2008

In this paper, a sample design of I/O port of micro-processor using ODC(Output Don't Care) computation that is one of methods for Clock Gating applicable at the register transfer level(RTL). The ODC computation Method is applied at the point that estimate the value considering Don't Care Conditions from output of datapath to registers using clock in logic system. This paper also shows the results of reduce consumption power due to controlling clock that was supplied at registers. In Experimental results, ODC computation Method reduce power reductions of around 37.5%

• Transactions of the Korean Society of Mechanical Engineers B
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• v.31 no.9
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• pp.814-821
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• 2007

A hybrid method is presented for efficient computation of turbulent flow noise at low Mach numbers. In this method, the turbulent flow field is computed by incompressible large eddy simulation (LES), while the acoustic field is computed with the linearized perturbed compressible equations (LPCE) derived in this study. Since LPCE is computed on the rather coarse acoustic grid with the flow variables and source term obtained by the incompressible LES, the computational efficiency of calculation is greatly enhanced. Furthermore, LPCE suppress the instability of perturbed vortical mode and therefore secure consistent and stable acoustic solutions. The proposed LES/LPCE hybrid method is applied to three low Mach number turbulent flow noise problems: i) circular cylinder, ii) isolated flat plate, and iii) interaction between cylinder wake and airfoil. The computed results are closely compared with the experimental measurements.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.986-992
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• 2021

To stabilize closed-loop wireless control systems, the state-of-the-art approach receives the individual sensor measurements at the controller and then sends the computed control signal to the actuators. We propose an over-the-air controller scheme where all sensors attached to the plant transmit scaled sensing signals simultaneously to the actuator, and the actuator then computes the feedback control signal by scaling the received signal. The over-the-air controller essentially adopts the over-the-air computation concept to compute the control signal for closed-loop wireless control systems. In contrast to the state-of-the-art sensor-to-controller and controller-to-actuator communication approach, the over-the-air controller exploits the superposition properties of multiple-access wireless channels to complete the communication and computation of a large number of sensing signals in a single communication resource unit. Therefore, the proposed scheme can obtain significant benefits in terms of low actuation delay and low resource utilization with a simple network architecture that does not require a dedicated controller.