• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.2977-2997
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• 2018

In big data era, fresh data grows rapidly every day. More than 30,000 gigabytes of data are created every second and the rate is accelerating. Many organizations rely heavily on real time streaming, while big data stream computing helps them spot opportunities and risks from real time big data. Storm, one of the most common online stream computing platforms, has been used for big data stream computing, with response time ranging from milliseconds to sub-seconds. The performance of Storm plays a crucial role in different application scenarios, however, few studies were conducted to evaluate the performance of Storm. In this paper, we investigate the performance of Storm under different application scenarios. Our experimental results show that throughput and latency of Storm are greatly affected by the number of instances of each vertex in task topology, and the number of available resources in data center. The fault-tolerant mechanism of Storm works well in most big data stream computing environments. As a result, it is suggested that a dynamic topology, an elastic scheduling framework, and a memory based fault-tolerant mechanism are necessary for providing high throughput and low latency services on Storm platform.

• International Journal of Advanced Culture Technology
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• 제3권1호
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• pp.113-119
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• 2015

This paper presents a design and implementation of real time electrical energy computing tool to measure and record the electrical energy based on type of detection devices, Hall Effect current sensor and Microcontroller. The tool was installed on the system power supply of the room and compared with kWh meter. Finally, we found that the energy record has error of average power calculating results is 0.077%.

• Journal of Computing Science and Engineering
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• 제1권1호
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• pp.56-73
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• 2007

Demands have been growing in safety-critical application fields for producing networked real-time embedded computing (NREC) systems together with acceptable assurances of tight service time bounds (STBs). Here a service time can be defined as the amount of time that the NREC system could take in accepting a request, executing an appropriate service method, and returning a valid result. Enabling systematic composition of large-scale NREC systems with STB certifications has been recognized as a highly desirable goal by the research community for many years. An appealing approach for pursuing such a goal is to establish a hard-real-time (HRT) component model that contains its own STB as an integral part. The TMO (Time-Triggered Message-Triggered Object) programming scheme is one HRT distributed computing (DC) component model established by the first co-author and his collaborators over the past 15 years. The TMO programming scheme has been intended to be an advanced high-level RT DC programming scheme that enables development of NREC systems and validation of tight STBs of such systems with efforts far smaller than those required when any existing lower-level RT DC programming scheme is used. An additional goal is to enable maximum exploitation of concurrency without damaging any major structuring and execution approaches adopted for meeting the first two goals. A number of previously untried program structuring approaches and execution rules were adopted from the early development stage of the TMO scheme. This paper presents new concrete justifications for those approaches and rules, and also discusses new extensions of the TMO scheme intended to enable further exploitation of concurrency in NREC system design and programming.

• 한국전자통신학회논문지
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• 제5권6호
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• pp.678-685
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• 2010

최근에 급성장하고 있는 실시간 통신 분산 컴퓨팅은 최근에 컴퓨터 응용분야의 하나로서 컴퓨터 과학과 공학 분야에서 급성장하고 있는 한 분야이다. 실시간 객체 지향 분산 컴퓨팅은 분산된 컴퓨터 시스템에서 객체 네트워크의 형태로 구성된 실시간 분산 컴퓨팅이다. 본 논문에서는 TMO 구조를 이용하여 실시간 통신 시뮬레이션 프로그래밍을 하기 위해 환자 모니터 원격 진료 시스템 응용 환경에 적용하였다. Central Monitor로부터 전송되어진 환자의 생체정보 Raw Data가 HIS의 데이터 수신 모듈을 통해 사용가능한 데이터로 재구성될 수 있도록 설계가 이루어져 있다. 환자 생체정보에 대한 실시간성과 생체정보에 대한 생체정보 데이터의 연속성을 부여함으로서 베드 사이트의 환자에게서 발생된 모든 생체정보에 의해 환자 관리가 이루어진다.

• 대한음성학회지:말소리
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• 제44호
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• pp.93-104
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• 2002

There are many speech analysis tools available. Among them real-time analysis tool is very useful for interactive experiments. A real-time speech analysis tool was implemented using Matlab. Matlab is a very widely used general purpose signal processing tool. In general, its computational speed is relatively lower than that of the codes from conventional programming languages. Especially, real-time analysis including input of signal and output of the result was not possible in the past. However, due to the improvement of computing power of PCs and inclusion of real-time I/O toolboxes in Matlab, real-time analysis is now possible in some extent by Matlab only. In this experiment, we tried to implement a real-time speech analysis tool using Matlab. Pitch and spectral information is computed in real-time. From the result it is shown that such real-time applications can be implemented easily using Matlab.

• 제어로봇시스템학회논문지
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• 제13권11호
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• pp.1074-1081
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• 2007

This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

• 한국컴퓨터정보학회논문지
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• 제21권1호
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• pp.85-90
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• 2016

In this paper, the biometric data is transmitted in real time from the IoT environment is runoff, forgery, alteration, prevention of the factors that can be generated from a denial-of-service in advance, and the security strategy for the biometric data to protect the biometric data secure from security threats offer. The convenience of living in our surroundings to life with the development of ubiquitous computing and smart devices are available in real-time. And is also increasing interest in the IOT. IOT environment is giving the convenience of life. However, security threats to privacy also are exposed for 24 hours. This paper examines the security threats to biological data to be transmitted in real time from IOT environment. The technology for such security requirements and security technology according to the analysis of the threat. And with respect to the biometric data transmitted in real time on the IoT environment proposes a security strategy to ensure the stability against security threats and described with respect to its efficiency.

• 한국산학기술학회논문지
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• 제10권9호
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• pp.2354-2360
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• 2009

유비쿼터스 컴퓨팅 환경에서 가장 널리 사용 가능한 분야는 헬스케어 분야이다. 본 논문에서는 유비쿼터스 환경에서 마이닝 기반 멀티 에이전트 헬스케어 시스템을 제안한다. 제안하는 기법은 환자의 몸으로부터 생성된 센싱 데이터를 마이닝을 이용하여 진단 패턴을 뽑아내어 정상 상태, 긴급 상태, 응급 상황으로 분류할 수 있다. 이는 실시간으로 센싱되는 엄청난 양의 생체 데이터를 처리할 수 있으며, 환자의 병력 데이터와 비교, 분석한다. 이를 위해 연관 규칙 탐사를 2가지 데이터 그룹으로 구분하여 적용한다. 첫 번째는, 기존의 방대한 의료 병력 데이터로 두 번째는, 체온, 혈압, 맥박등과 같은 센서로부터 센싱한 환자의 실시간 생체데이터로 분류한다. 제안하는 시스템은 PDA 같은 모바일 디바이스 등을 통하여 병원과 멀리 떨어진 지역에서도 긴급 상황을 판단하여 처리할 수 있다. 또한 환자(노인)의 상태를 실시간으로 모니터링 함으로써 요구되는 시간과 비용을 단축하게 되고, 의료 서비스의 지원에 대한 효율성을 높이게 된다.

• Journal of Computing Science and Engineering
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• 제8권1호
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• pp.34-42
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• 2014

Time-predictability of computing is critical for hard real-time and safety-critical systems. However, currently there is no metric available to quantitatively evaluate time-predictability, a feature crucial to the design of time-predictable processors. This paper first proposes the concept of architectural time-predictability, which separates the time variation due to hardware architectural/microarchitectural design from that due to software. We then propose the standard deviation of clock cycles per instruction (CPI), a new metric, to measure architectural time-predictability. Our experiments confirm that the standard deviation of CPI is an effective metric to evaluate and compare architectural time-predictability for different processors.

• 한국정보과학회논문지:데이타베이스
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• 제32권2호
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• pp.142-150
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• 2005

공유 디스크(Shared Disks: SD) 클러스터는 다수 개의 처리 노드를 연동하는 방식으로, 각 노드는 디스크 계층에서 데이타베이스를 공유한다. 고성능의 트랜잭션 처리를 위한 SD 클러스터의 효율성은 기존의 연구들을 통해서 입증되었으나, SD 클러스터 기반의 실시간 처리에 대한 연구는 지금까지 이루어지지 않았다. 실시간 트랜잭션의 경우 전통적인 트랜잭션의 ACID 속성 외에 시간 제약성을 추가로 가진다. 클러스터 기술을 실시간 트랜잭션 처리에 도입함으로써 높은 가용성과 노드들 사이의 병렬성에 따른 성능 향상을 기대할 수 있다. 이런 관점에서 본 논문에서는 먼저 SD 클러스터 기반 실시간 데이터베이스 시스템의 실험 모형을 개발한다. 그리고 개발한 모형을 기반으로 실시간 트랜잭션 처리를 위한 SD 클러스터의 적합성 여부를 평가한다. 뿐만 아니라 실시간 트랜잭션 처리 알고리즘과 SD 클러스터 알고리즘들 간의 상호 영향에 대해 다양한 실험을 통하여 평가한다.