• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4349-4371
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• 2019

Moldable parallel tasks are widely used in different areas, such as weather forecast, biocomputing, mechanical calculation, and so on. Considering the deadline and the speedup, scheduling moldable parallel tasks becomes a difficulty. Past work majorly focuses on the LA (List Algorithms) or OMA (Optimizing the Middle Algorithms). Different from prior work, our work normalizes execution time and makes all tasks have the same scope in normalized execution time: [0,1], and then according to the normalized execution time, a method is used to search for the reference execution time without considering the deadline of tasks. According to the reference execution time, we get an initial scheduling result based on AFCFS (Adaptive First Comes First Served) policy. Finally, a heuristic approach is used to improve the performance of the initial scheduling result. We call our method HSRET (a Heuristic Scheduling method based on Reference Execution Time). Comparisons to other methods show that HSRET has good performance in AWT (Average Waiting Time), AET (Average Execution Time), and PUT (Percentages of Unfinished Tasks).

• 인터넷정보학회논문지
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• 제17권4호
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• pp.51-60
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• 2016

내장 소프트웨어는 실시간성 및 실행 환경으로부터의 독립성을 요구사항으로 갖는다. 실시간성 요구사항은 탑재된 태스크의 최악 실행 시간으로부터 영향을 받는다. 따라서 실시간성을 보장하기 위해서는 정적 분석 기반의 최악 실행 시간 분석 방법을 사용하여 프로그램의 최악 실행 시간을 파악하여야 한다. 그러나 기존의 최악 실행 시간 분석은 실행 환경으로부터 독립성을 고려하지 않는다. 이에 우리는 실행 환경으로부터 독립성을 제공하기 위해 소스코드로부터 실행 시간을 측정하는 방법을 제시한다. 이를 위해 실행 코드가 아닌 소스코드로부터 생성된 제어 흐름 그래프를 통해 실행 시간을 측정한다. 또한 소스코드로부터 생성된 제어 흐름 그래프에는 실행 시간 정보가 존재하지 않기 때문에, 이를 제공하기 위해 소스코드의 문장과 실행코드의 명령어와의 관계를 분석한다. 결과적으로 실행 시간 측정이 가능한 제어 흐름 그래프를 생성할 수 있다. 이를 통해 프로세서로부터 종속적인 부분을 매개변수화할 수 있기 때문에, 최악 실행 시간 분석 도구의 유연성을 향상시킬 수 있다.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.49-60
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• 2023

The amount of data generated by electronic systems through e-commerce, social networks, and data computation has risen. However, the security of data has always been a challenge. The problem is not with the quantity of data but how to secure the data by ensuring its confidentiality and privacy. Though there are several research on cloud data security, this study proposes a security scheme with the lowest execution time. The approach employs a non-linear time complexity to achieve data confidentiality and privacy. A symmetric algorithm dubbed the Non-Deterministic Cryptographic Scheme (NCS) is proposed to address the increased execution time of existing cryptographic schemes. NCS has linear time complexity with a low and unpredicted trend of execution times. It achieves confidentiality and privacy of data on the cloud by converting the plaintext into Ciphertext with a small number of iterations thereby decreasing the execution time but with high security. The algorithm is based on Good Prime Numbers, Linear Congruential Generator (LGC), Sliding Window Algorithm (SWA), and XOR gate. For the implementation in C, thirty different execution times were performed and their average was taken. A comparative analysis of the NCS was performed against AES, DES, and RSA algorithms based on key sizes of 128kb, 256kb, and 512kb using the dataset from Kaggle. The results showed the proposed NCS execution times were lower in comparison to AES, which had better execution time than DES with RSA having the longest. Contrary, to existing knowledge that execution time is relative to data size, the results obtained from the experiment indicated otherwise for the proposed NCS algorithm. With data sizes of 128kb, 256kb, and 512kb, the execution times in milliseconds were 38, 711, and 378 respectively. This validates the NCS as a Non-Deterministic Cryptographic Algorithm. The study findings hence are in support of the argument that data size does not determine the execution.

• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.49-56
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• 2023

Computer architecture serves as a link between application requirements and underlying technology capabilities such as technical, mathematical, medical, and business applications' computational and storage demands are constantly increasing. Machine learning these days grown and used in many fields and it performed better than traditional computing in applications that need to be implemented by using mathematical algorithms. A mathematical algorithm requires more extensive and quicker calculations, higher computer architecture specification, and takes longer execution time. Therefore, there is a need to improve the use of computer hardware such as CPU, memory, etc. optimization has a main role to reduce the execution time and improve the utilization of computer recourses. And for the importance of execution time in implementing machine learning supervised module linear regression, in this paper we focus on optimizing machine learning algorithms, for this purpose we write a (Diabetes prediction program) and applying on it a Practical Swarm Optimization (PSO) to reduce the execution time and improve the utilization of computer resources. Finally, a massive improvement in execution time were observed.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권7호
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• pp.510-514
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• 2009

기존의 실시간 시스템들이 SOA기반으로 통합되면 실시간 SOA가 필요하다. 실시간 SOA에서 하나의 서비스는 일반적으로 여러 개의 작은 단위서비스로 분화되기도 한다. 단위서비스의 예측실행시간은 제공자시스템에서 제공된다. 하지만 요청자는 중개자와 제공자 사이의 메시지 송수신 과정에 관여되는 시간요소를 분석한 시간예측도 필요하다. 본 논문은 웹 서비스의 QoS 만족도를 높이기 위해서 트랜잭션을 고려한 시간 예측과 더불어 다중처리기 시스템의 보편화에 따른 트랜잭션의 실행시간 예측에 관련된 시간요소를 분석하여 개선된 최악의 실행시간 예측 방법을 제안한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
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• pp.1379-1382
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• 2003

Recently, mobile embedded systems used widly in various applications. Managing power consumption is becoming a matter of primary concern because those systems use limited power supply. As an approach reduce power consumption, voltage can be scaled down. according to the execution time and deadline. By reducing the supplying voltage to 1/N power consumption can be reduced to 1/N. DPM-S is a well known method for dynamic voltage scaling. In this paper, we enhanced DPM-S by using average execution time aggressively. The frequency of processor is calculated based in average execution time instead of worst case execution time. Simulation results show that our method achieve up to 5％ energy savings than DPM-S.

• 정보처리학회논문지A
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• 제8A권2호
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• pp.117-124
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• 2001

At NOW (Networks Of Workstations), the load sharing is very important role for improving the performance. The known load sharing strategy is fixed-granularity, variable-granularity and adaptive-granularity. The variable-granularity algorithm is sensitive to the various parameters. But Send algorithm, which implements the fixed-granularity strategy, is robust to task granularity. And the performance difference between Send and variable-granularity algorithm is not substantial. But, in Send algorithm, the computing time and the communication time are not overlapped. Therefore, long latency time at the network has influence on the execution time of the parallel program. In this paper, we propose the preSend algorithm. In the preSend algorithm, the master node can send the data to the slave nodes in advance without the waiting for partial results from the slaves. As the master node sent the next data to the slaves in advance, the slave nodes can process the data without the idle time. As stated above, the preSend algorithm can overlap the computing time and the communication time. Therefore we reduce the influence of the long latency time at the network and the execution time of the parallel program on the NOW. To compare the execution time of two algorithms, we use the $320{\times}320$ matrix multiplication. The comparison results of execution times show that the preSend algorithm has the shorter execution time than the Send algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권1호
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• pp.36-43
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• 2016

The transformation time among queries in the database management system (DBMS) is responsible for the execution time of users' queries, because a conventional DBMS does not consider the transformation cost when queries are transformed for execution. To reduce the transformation time (cost reduction) during execution, we propose an optimal query transformation method by exploring queries from a cost-based point of view. This cost-based point of view means considering the cost whenever queries are transformed for execution. Toward that end, we explore and compare set off heuristic, linear, and exhaustive cost-based transformations. Further, we describe practical methods of cost-based transformation integration and some query transformation problems. Our results show that, some cost-based transformations significantly improve query execution time. For instance, linear and heuristic transformed queries work 43% and 74% better than exhaustive queries.

• 정보처리학회논문지A
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• 제12A권5호
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• pp.365-374
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• 2005

신뢰성 있는 내장 실시간 시스템을 구축하기 위해서는 프로그램의 스케줄링 가능성 여부를 검증해야 한다 스케줄링 가능성 분석을 위해서 는 프로그램의 최악실행시간 정보가 필수적인 요소이다. 최악실행시간 분석은 두 단계로 나된다. 첫 번째 단계에서는 프로그램 언어 구문상의 흐름을 분석하고, 두 번째 단계에서는 수행되는 흐름 경로상의 하드웨어적인 요소를 고려하여 수행시간을 분석한다. 본 논문에서는 XScale 프로세서를 대상으로 하는 최악실행시간 통합 분석 도구인 WATER(WCET Analysis Tool for Embedded Real-time system)를 설계하고 구현한다. 상위 수준의 흐름 분석기와 하위 수준의 실행시간 분석기로 이루어진 WATER의 구조를 소개하고 소프트웨어의 실제 측정과 WATER의 분석 결과를 비교한다.

• 한국정보과학회논문지:시스템및이론
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• 제29권11호
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• pp.601-610
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• 2002

태스크내부에서 공급 전압을 조절하는 태스크내 전압 스케쥴링(IntraVS)은 저전력 프로그램을 구현하는 데 효과적인 방법이다. 본 논문에서는 경성 실시간 응용프로그램에서 평균 실행 시간에 대한 정보를 이용하여 전력 소모를 효과적으로 줄이는 새로운 태스크내 전압 스케쥴링 알고리즘을 제시한다. 최악 실행 시간을 사용하여 전압 조절의 결정을 내렸던 기존의 태스크내 전압 스케줄링과는 달리, 제안된 알고리즘은 평균 실행 시간에 바탕을 두고 실행 속도를 조절함으로써 주어진 시간 제약 조건을 만족시키면서도 기존 방법보다 에너지 효율성을 높일 수 있다. MPEG-4 디코더를 이용한 실험 결과, 제안된 알고리즘은 기존의 태스크내 전압 스케줄링에 비해서 전력 소모를 최대 34% 감소시켰다.