• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.313-320
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• 2005

The increasing popularity of multimedia streaming services introduces new challenges in content distribution. Especially, it is important to provide the QoS guarantees as they are increasingly expected to support the multimedia applications. Multimedia streams typically experience the high start-up delay due to the large protocol overhead, the delay, and the loss properties of the wireless networks. The service providers can improve the performance of multimedia streaming by caching the initial segment (prefix) of the popular streams at proxies near the requesting clients. The proxy can initiate transmission to the client while requesting the remainder of the stream from the server. In this paper, we propose the traffic based caching algorithm (TSLRU) to improve the performance of caching proxy. TSLRU classifies the traffic into three types, and improve the performance of caching proxy by reflecting the several elements such as traffic types, recency, frequency, object size when performing the replacement decision. In simulation, TSLRU performs better than the existing schemes in terms of byte hit rate, hit rate, startup latency, and throughput.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.303-310
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• 2002

In this paper, we propose a proxy caching scheme that stores a portion of a continuous media object or an entire object on the Internet. The proxy stores the initial fraction of a continuous media object and determines the optimal size of the initial fraction of the continuous media object to be cached based on the object popularity. Under the proposed scheme, the initial latency of most clients and the data transferred from a remote server can be reduced and limited cache storage space can be utilized efficiently. Considering the characteristics of continuous media, we also propose the novel popularity for the continuous media objects based on the amount of the data of each object played by the clients. Finally, we have performed trace-driven simulations to evaluate our caching scheme and the popularity for the continuous media objects. Through these simulations, we have verified that our caching scheme, PPC outperforms other well-known caching schemes in terms of BHR, DSR and replacement and that popularity for the continuous media objects based on the amount of the playback data can enhance the performance of caching scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8A
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• pp.820-826
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• 2007

This paper proposes an enhanced degree computationless modified Euclid's(E-DCME) algorithm and its architecture for Reed-Solomon decoders. The proposed E-DCME algorithm has shorter critical path delay that is $T_{mult}+T_{add}+T_{mux}$ compared with the existing modified Euclid's algorithm and the degree computationless modified Euclid's(DCME) algorithm since it uses new initial conditions. The proposed E-DCME architecture employing a systolic array requires only 2t-1 clock cycles to solve the key equation without initial latency. In addition, the E-DCME architecture consisting of 3t basic cells has regularity and scalability since it uses only one processing element. The E-DCME architecture using the $0.18{\mu}m$ Samsung standard cell library consists of 18,000 gates.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.7
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• pp.518-525
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• 2003

In this paper, we present a fast hardware architecture to implement a parallel 2-dimensional discrete wavelet transform(DWT)based on the lifting scheme DWT framework. The conventional 2-D DWT had a long initial and total latencies to get the final 2D transformed coefficients because the DWT used an entire input data set for the transformation and transformed sequentially The proposed architecture increased the parallel performance at computing the row directional transform using new data splitting method. And, we used the hardware resource sharing architecture for improving the total throughput of 2D DWT. Finally, we proposed a scheduling of hardware resource which is optimized to the proposed hardware architecture and splitting method. Due to the use of the proposed architecture, the parallel computing efficiency is increased. This architecture shows the initial and total latencies are improved by 50% and 66%.

• Journal of The Korean Association of Information Education
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• v.4 no.2
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• pp.140-146
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• 2001

Scheduling strategy in the Education-on-Demand system should be designed to service the isochronous requests from several learners with single disk retrieval to improve the performance of the system. In this paper, the scheduling strategy which reduces the disk I/O and buffer consumption by utilizing the resources of the learner's system has been proposed. All the requests from the learner are not serviced from the server but forwarded to the learner's system which preserves the requested information. Therefore, the server can increase the throughput and reduces the initial latency time of the user. The proposed strategy has been compared to the conventional method by simulations and proved to be more efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3208-3229
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• 2017

Rectification is an essential procedure for simplifying the disparity extraction of stereo matching algorithms by removing vertical mismatches between left and right images. To support real-time stereo matching, studies have introduced several look-up table (LUT)- and computational logic (CL)-based rectification approaches. However, to support high-resolution images, the LUT-based approach requires considerable memory resources, and the CL-based approach requires numerous hardware resources for its circuit implementation. Thus, this paper proposes a multi-level accumulation-based rectification method as a simple CL-based method and its circuit implementation. The proposed method, which includes distortion correction, reduces addition operations by 29%, and removes multiplication operations by replacing the complex matrix computations and high-degree polynomial calculations of the conventional rectification with simple multi-level accumulations. The proposed rectification circuit can rectify $1,280{\times}720$ stereo images at a frame rate of 135 fps at a clock frequency of 125 MHz. Because the circuit is fully pipelined, it continuously generates a pair of left and right rectified pixels every cycle after 13-cycle latency plus initial image buffering time. Experimental results show that the proposed method requires significantly fewer hardware resources than the conventional method while the differences between the results of the proposed and conventional full rectifications are negligible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.651-669
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• 2013

In this paper, we study a novel routing algorithm based on load balancing for multi-channel wireless mesh networks. In order to increase the network capacity and reduce the interference of transmission streams and the communication delay, on the basis of weighted cumulative expected transmission time (WCETT) routing metric this paper proposes an improved routing metric based on load balancing and channel interference (LBI_WCETT), which considers the channel interference, channel diversity, link load and the latency brought by channel switching. Meanwhile, in order to utilize the multi-channel strategy efficiently in wireless mesh networks, a new channel allocation algorithm is proposed. This channel allocation algorithm utilizes the conflict graph model and considers the initial link load estimation and the potential interference of the link to assign a channel for each link in the wireless mesh network. It also utilizes the channel utilization percentage of the virtual link in its interference range as the channel selection standard. Simulation results show that the LBI_WCETT routing metric can help increase the network capacity effectively, reduce the average end to end delay, and improve the network performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.419-421
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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.

• 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 Korea Society of Industrial Information Systems
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• v.18 no.6
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• pp.31-37
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• 2013

Modern graphic processors, multimedia processors and audio processors mostly use floating-point number. High-level language such as C and Java use both single precision and double precision floating-point number. In this paper, an algorithm which computes the reciprocal of double precision floating-point number using a 32 bit multiplier is proposed. It divides the mantissa of double precision floating-point number to upper part and lower part, and calculates the reciprocal of the upper part with Newton-Raphson algorithm. And it computes the reciprocal of double precision floating-point number with calculated upper part reciprocal as the initial value. Since the number of multiplications performed by the proposed algorithm is dependent on the mantissa of floating-point number, the average number of multiplications per an operation is derived from some reciprocal tables with varying sizes.