• Title/Summary/Keyword: Algorithm Execution time

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Refined fixed granularity algorithm on Networks of Workstations (NOW 환경에서 개선된 고정 분할 단위 알고리즘)

  • Gu, Bon-Geun
    • The KIPS Transactions:PartA
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    • v.8A no.2
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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.

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Ensuring Data Confidentiality and Privacy in the Cloud using Non-Deterministic Cryptographic Scheme

  • John Kwao Dawson;Frimpong Twum;James Benjamin Hayfron Acquah;Yaw Missah
    • International Journal of Computer Science & Network Security
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    • v.23 no.7
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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.

A Dynamic Voltage Scaling Algorithm for Low-Energy Hard Real-Time Applications using Execution Time Profile (실행 시간 프로파일을 이용한 저전력 경성 실시간 프로그램용 동적 전압 조절 알고리즘)

  • 신동군;김지홍
    • Journal of KIISE:Computer Systems and Theory
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    • v.29 no.11
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    • pp.601-610
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    • 2002
  • Intra-task voltage scheduling (IntraVS), which adjusts the supply voltage within an individual task boundary, is an effective technique for developing low-power applications. In this paper, we propose a novel intra-task voltage scheduling algorithm for hard real-time applications based on average-case execution time. Unlike the conventional IntraVS algorithm where voltage scaling decisions are based on the worst-case execution cycles, tile proposed algorithm improves the energy efficiency by controlling the execution speed based on average-case execution cycles while meeting the real-time constraints. The experimental results using an MPEG-4 decoder program show that the proposed algorithm reduces the energy consumption by up to 34% over conventional IntraVS algorithm.

Image Segmentation Using an Extended Fuzzy Clustering Algorithm (확장된 퍼지 클러스터링 알고리즘을 이용한 영상 분할)

  • 김수환;강경진;이태원
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.3
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    • pp.35-46
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    • 1992
  • Recently, the fuzzy theory has been adopted broadly to the applications of image processing. Especially the fuzzy clustering algorithm is adopted to image segmentation to reduce the ambiguity and the influence of noise in an image.But this needs lots of memory and execution time because of the great deal of image data. Therefore a new image segmentation algorithm is needed which reduces the memory and execution time, doesn't change the characteristices of the image, and simultaneously has the same result of image segmentation as the conventional fuzzy clustering algorithm. In this paper, for image segmentation, an extended fuzzy clustering algorithm is proposed which uses the occurence of data of the same characteristic value as the weight of the characteristic value instead of using the characteristic value directly in an image and it is proved the memory reduction and execution time reducted in comparision with the conventional fuzzy clustering algorithm in image segmentation.

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Lightweight Algorithm for Digital Twin based on Diameter Measurement using Singular-Value-Decomposition (특이값 분해를 이용한 치수측정 기반 디지털 트윈 알고리즘 경량화)

  • Seungmin Lee;Daejin Park
    • IEMEK Journal of Embedded Systems and Applications
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    • v.18 no.3
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    • pp.117-124
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    • 2023
  • In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.

Shortest-Frame-First Scheduling Algorithm of Threads On Multithreaded Models (다중스레드 모델에서 최단 프레임 우선 스레드 스케줄링 알고리즘)

  • Sim, Woo-Ho;Yoo, Weon-Hee;Yang, Chang-Mo
    • Journal of KIISE:Software and Applications
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    • v.27 no.5
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    • pp.575-582
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    • 2000
  • Because FIFO thread scheduling used in the existing multithreaded models does not consider locality in programs, it may result in the decrease of the performance of execution, caused by the frequent context switching overhead and delay of execution of relatively short frames. Quantum unit scheduling enhances the performance a little, but it still has the problems such as the decrease in the processor utilization and the longer delay due to its heavy dependency on the priority of the quantum units. In this paper, we propose shortest-frame-first(SFF) thread scheduling algorithm. Our algorithm selects and schedules the frame that is expected to take the shortest execution time using thread size and synchronization information analyzed at compile-time. We can estimate the relative execution time of each frame at compile-time. Using SFF thread scheduling algorithm on the multithreaded models, we can expect the faster execution, better utilization of the processor, increased throughput and short waiting time compared to FIFO scheduling.

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Computer Architecture Execution Time Optimization Using Swarm in Machine Learning

  • Sarah AlBarakati;Sally AlQarni;Rehab K. Qarout;Kaouther Laabidi
    • International Journal of Computer Science & Network Security
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    • v.23 no.10
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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.

A Study on Binarization of Handwritten Character Image (필기체 문자 영상의 이진화에 관한 연구)

  • 최영규;이상범
    • Journal of the Korea Computer Industry Society
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    • v.3 no.5
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    • pp.575-584
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    • 2002
  • On-line handwritten character recognition be achieved successful results since effectively neural networks divided the letter which is the time ordering of strokes and stroke position. But off-line handwritten character recognition is in difficulty of incomplete preprocessing because has not information of motion or time and has frequently overlap of the letter and many noise occurrence. consequently off-line handwritten character recognition needs study of various methods. This paper apply watershed algorithm to preprocessing for off-line handwritten hangul character recognition. This paper presents effective method in four steps in watershed algorithm as consider execution time of watershed algorithm and quality of result image. As apply watershed algorithm with effective structure to preprocessing, can get to the good result of image enhancement and binarization. In this experiment, this paper is estimate the previous method with this paper method for execution time and quality in image. Average execution time on the previous method is 2.16 second and Average execution time on this paper method is 1.72 second. While this paper method is remove noise effectively with overlap stroke, the previous method does not seem to be remove noise effectively with overlap stroke.

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Effect of Execution Time-oriented Python Sort Algorithm Training on Logical Thinking Ability of Elementary School Students (수행시간 중심의 파이썬 정렬 알고리즘 교육이 초등학생 논리적 사고력에 미치는 효과)

  • Yang, Yeonghoon;Moon, Woojong;Kim, Jonghoon
    • Journal of The Korean Association of Information Education
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    • v.23 no.2
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    • pp.107-116
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    • 2019
  • The purpose of this study is to develop a Python sorting algorithm training program based on execution time as an educational method for enhancing the logical thinking power of elementary students and then to verify the effect. The education program was developed based on the results of the pre-demand analysis conducted on 100 elementary school teachers. In order to verify the effectiveness of the developed educational program, I teached 25 students of the volunteer sample of the elementary school education donation program conducted at ${\bigcirc}{\bigcirc}$ University conducted 42 hours, 7 days. The results of the pre-test and post-test were analyzed using the 'Group Assessment of Logical Thinking(GALT)' developed by the Korea Educational Development Institute. The results showed that the Python sorting algorithm training centered on execution time was effective in improving the logical thinking ability of elementary school students.

Evaluation of Network Reliability Using Most Probable States

  • Oh, Dae-Ho;Park, Dong-Ho;Lee, Seung-Min
    • Proceedings of the Korean Reliability Society Conference
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    • 2001.06a
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    • pp.463-469
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    • 2001
  • An algorithm is presenter for generating the most probable states in decreasing order of probability of each unit. The proposed new algorithm in this note is compared with the existing methods regarding memory requirement and execution time. Our method is simpler and, judging from the computing experiment, it requires less memory size than the previously known methods and takes comparable execution time to previous methods for an acceptable level of criterion.

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