• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.123-124
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• 2013

비용대비 작업 처리의 효율을 위해서는 사용자들의 작업 요구사항에 적절한 자원을 선택하고 요구 작업을 적절한 할당된 자원에 스케쥴링하는 플랫폼이 필수적이다. 또한 이러한 플랫폼은 사용자의 SLA 에 따라 작업 처리 기한 안에 요구 비용 이내로 작업을 처리할 수 있도록 결정을 내릴 수 있어야 하고 요구 작업량의 변화에 따라 즉각 대응을 하기 위하여 실시간적인 결정을 내릴 수 있어야 한다. 이러한 복잡한 결정 사항들을 최적 판단으로 대신 처리해주는 미들웨어로 클라우드 자원 브로커 시스템을 사용할 수 있다. 클라우드 자원 브로커 시스템은 작업 스케쥴링과 자원 프로비저닝 등이 가격, 처리시간에 중요한 선택 및 수행을 한다. 기존의 많은 논문들에서의 작업 스케줄링은 다중 테넌트 정책의 클라우드가 제공하는 사용자들간의 가상 머신 독립에 초점을 두어 하나의 가상 머신이 하나의 작업에 한정되도록 처리하는 방식이었다. 이는 병렬화의 정도가 낮은 어플리케이션의 경우 시스템 활용률이 낮아 자원 활용율이 떨어진다. 이를 다수의 작업을 멀티 태스킹, 멀티 스레드의 방법으로 하나의 가상 머신에서 처리하도록 하여 스레드 레벨 병렬화의 이점을 이용해 자원 이용률을 높임으로 효율을 높이고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1595-1598
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• 2010

임베디드 시스템의 설계 복잡도가 높아지고, 설계 확인 및 수정 비용이 증가하면서 목표 아키텍처가 결정되기 전, 즉 시스템의 설계 초기 단계에서의 적절한 소프트웨어 검증이 더욱 더 중요해지고 있다. 이러한 초기 단계의 시뮬레이션은 높은 성능을 보이면서도 기능과 타이밍, 하드웨어 아키텍처, 태스크 할당, 그리고 스케줄링 정책 등을 잘 반영해야 한다. 특히 외부와의 시간 의존적인 상호 작용이 있는 경우 이를 반영하는 것은 어려운 문제인데 기존 연구[1]에서는 반복 시뮬레이션을 통해 이를 반영할 수 있도록 하였으나, 시뮬레이션 결과의 수렴 속도에 따라 총 시뮬레이션 시간이 증가한다는 약점이 있었다. 본 연구에서는 시스템의 명세 조건에 따라, 가능한 경우 반복 시뮬레이션을 피하고 단일 시뮬레이션만으로 시뮬레이션 결과를 얻음으로써 시뮬레이션 시간을 크게 단축할 수 있는 방법을 제시하였다. 연구의 결과는 반복 시뮬레이션 예제, 로봇 예제, 센서 네트워크 예제 등의 예제를 통해 검증되었으며 시뮬레이션 성능은 평균적으로 약 2.31 배 향상되었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.220-223
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• 2011

For successfully commercialized grid systems, it is required to provide an efficient scheduling scheme which is able to optimize benefits for three participants such as consumers, brokers, and providers so that every participant has sufficient benefit to maintain a sustainable market. In this paper, we define this job scheduling problem as an objective optimization problem for three participants. The three objectives are to maximize the success rate of job execution, total achieved profit, and the system utilization. To address the scheduling problem, we propose heuristics referred to as SLA-aware scheduling scheme (SA) for optimal resource allocation. The simulation results show that the improvement and the effectiveness of the proposed scheme and the proposed scheme can outperform well-known scheduling schemes such as first come first serve (FCFS), shortest job first (SJF), and earliest deadline first (EDF).

• Journal of Korea Multimedia Society
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• v.4 no.1
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• pp.13-28
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• 2001

In a VOD(Vide-On-Demand) system, video data are generally stored in magnetic disk array. In order to provide real-time requirement for data retrieval, video streams must be delivered continuously to the clients such that the delivery of continuous media can be guaranteed in a timely fashion. Compared to the increased performance of processors and networks, the performance of magnetic disk systems have improved only modestly. In order to improve the performance of storage system, disk array system is proposed and used. The array system improves I/O performance by placing disks in parallel and retrieving data concurrently. In this paper, two approaches are considered in order to access the video data in a VOD system, which are CTL(Constant Time Length) and CDL(Constant Data Length) access policies. Disk scheduling policies are also classified into the two categories and compared in terms of the maximum allowable video streams with different degrees of disk array synchronization, under the mixed environments in which both data access policy and disk scheduling policy are considered. Among the compared scheduling policies, LOOK was shown to have the best performance. In terms of degree of disk synchronization, more gain was achieved with large degree of synchronization. In comparisons of performance of CTL and CDL, CTL was proved to have a little superior performance in terms of number of maximum allowable streams.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.137-148
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• 2012

Cloud service users request dedicated virtual computing resource from the cloud service provider to process jobs in independent environment from other users. To optimize this process with automated method, in this paper we proposed a framework for workflow scheduling in the cloud environment, in which the core component is the middleware called broker mediating the interaction between users and cloud service providers. To process jobs in on-demand and virtualized resources from cloud service providers, many papers propose scheduling algorithms that allocate jobs to virtual machines which are dedicated to one machine one job. With this method, the isolation of being processed jobs is guaranteed, but we can't use each resource to its fullest computing capacity with high efficiency in resource utilization. This paper therefore proposed a cost-efficient job scheduling algorithm which maximizes the utilization of managed resources with increasing the degree of multiprogramming to reduce the number of needed virtual machines; consequently we can save the cost for processing requests. We also consider the performance degradation in proposed scheme with thrashing and context switching. By evaluating the experimental results, we have shown that the proposed scheme has better cost-performance feature compared to an existing scheme.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.107-116
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• 2011

In this paper, a traffic adaptive sleep based medium access control (TAS-MAC) protocol for wireless sensor networks (WSNs) is proposed. The protocol aims for WSNs which consist of clustered sensor nodes and is based on TDMA-like schema. It is a typical schedule based mechanism which is adopted in previous protocols such as LEACH and Bit-Map Assisted MAC. The proposed MAC, however, considers unexpected long silent period in which sensor nodes have no data input and events do not happen in monitoring environment. With the simple traffic measurement, the TAS-MAC eliminates scheduling phases consuming energy in previous centralized approaches. A frame structure of the protocol includes three periods, investigation (I), transmission (T), and sleep-period (S). Through the I-period, TAS-MAC aggregates current traffic information from each end node and dynamically decide the length of sleep period to avoid energy waste in long silent period. In spite of the energy efficiency of this approach, the delay of data might increase. Thus, we propose an advanced version of TAS-MAC as well, each node in cluster sends one or more data packets to cluster head during the T-period of a frame. Through simulation, the performance in terms of energy consumption and transmission delay is evaluated. By comparing to BMA-MAC, the results indicate the proposed protocol is more energy efficient with tolerable expense in latency, especially in variable traffic situation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2935-2944
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• 2009

This paper proposes Dual DBR(Drum-Buffer-Rope) system for a small-to-medium-sized PCB(Printed Circuit Board) manufacturing line. DBR method of TOC(Theory of Constraints) is an effective system for a small-to-medium-sized company to build production scheduling system. But to apply it to PCB line, it needs more technical consideration because of multiple constraints, looping process line and complex buffer management. This paper proposes an answer of these problems using Dual DBR to build production scheduling system more successfully. And it was confirmed that lead time was reduced more than 20% applying Dual DBR system to a domestic PCB manufacturing line actually.

• Journal of the Korean Society for Railway
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• v.11 no.4
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• pp.364-370
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• 2008

In this paper, we proposed new sensor network architecture with autonomous robots based on beacon mode and implemented real time monitoring system in real test-bed environment. The proposed scheme offers beacon based real-time scheduling for reliable association process with parent nodes and dynamically assigns network address by using NAA (Next Address Assignment) mechanism. For the large scale multi-sensor processing, our real-time monitoring system accomplished the intelligent database processing, which can generate not only the alert messages to the civilians but also process various sensing data such as fire, air, temperature and etc. Moreover, we also developed mobile robot which can support network mobility. Though the performance evaluation by using real test-bed system, we illustrate that our proposed system demonstrates promising performance for emergence monitoring systems.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.9-26
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• 2005

In the pursuit of ever higher levels of performance, recent computer systems have made use of deep pipeline, dynamic scheduling and multi-issue superscalar processor technologies. In this situations, branch prediction schemes are an essential part of modem microarchitectures because the penalty for a branch misprediction increases as pipelines deepen and the number of instructions issued per cycle increases. In this paper, we propose a novel branch prediction scheme, direction-gshare(d-gshare), to improve the prediction accuracy. At first, we model a neural network with the components that possibly affect the branch prediction accuracy, and analyze the variation of their weights based on the neural network information. Then, we newly add the component that has a high weight value to an original gshare scheme. We simulate our branch prediction scheme using Simple Scalar, a powerful event-driven simulator, and analyze the simulation results. Our results show that, compared to bimodal, two-level adaptive and gshare predictor, direction-gshare predictor(d-gshare. 3) outperforms, without additional hardware costs, by up to 4.1% and 1.5% in average for the default mont of embedded direction, and 11.8% in maximum and 3.7% in average for the optimal one.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.337-347
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• 2007

An embedded system is called a multi-mode embedded system if it performs multiple applications by dynamically reconfiguring the system functionality. Further, the embedded system is called a multi-mode multi-task embedded system if it additionally supports multiple tasks to be executed in a mode. In this Paper, we address a HW/SW partitioning problem, that is, HW/SW partitioning of multi-mode multi-task embedded applications with timing constraints of tasks. The objective of the optimization problem is to find a minimal total system cost of allocation/mapping of processing resources to functional modules in tasks together with a schedule that satisfies the timing constraints. The key success of solving the problem is closely related to the degree of the amount of utilization of the potential parallelism among the executions of modules. However, due to an inherently excessively large search space of the parallelism, and to make the task of schedulabilty analysis easy, the prior HW/SW partitioning methods have not been able to fully exploit the potential parallel execution of modules. To overcome the limitation, we propose a set of comprehensive HW/SW partitioning techniques which solve the three subproblems of the partitioning problem simultaneously: (1) allocation of processing resources, (2) mapping the processing resources to the modules in tasks, and (3) determining an execution schedule of modules. Specifically, based on a precise measurement on the parallel execution and schedulability of modules, we develop a stepwise refinement partitioning technique for single-mode multi-task applications. The proposed techniques is then extended to solve the HW/SW partitioning problem of multi-mode multi-task applications. From experiments with a set of real-life applications, it is shown that the proposed techniques are able to reduce the implementation cost by 19.0% and 17.0% for single- and multi-mode multi-task applications over that by the conventional method, respectively.