• Title/Summary/Keyword: computing algorithm

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Parallel String Matching and Optimization Using OpenCL on FPGA (FPGA 상에서 OpenCL을 이용한 병렬 문자열 매칭 구현과 최적화 방향)

  • Yoon, Jin Myung;Choi, Kang-Il;Kim, Hyun Jin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.1
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    • pp.100-106
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    • 2017
  • In this paper, we propose a parallel optimization method of Aho-Corasick (AC) algorithm and Parallel Failureless Aho-Corasick (PFAC) algorithm using Open Computing Language (OpenCL) on Field Programmable Gate Array (FPGA). The low throughput of string matching engine causes the performance degradation of network process. Recently, many researchers have studied the string matching engine using parallel computing. FPGA's vendors offer a parallel computing platform using OpenCL. In this paper, we apply the AC and PFAC algorithm on DE1-SoC board with Cyclone V FPGA, where the optimization that considers FPGA architecture is performed. Experiments are performed considering global id, local id, local memory, and loop unrolling optimizations using PFAC algorithm. The performance improvement using loop unrolling is 129 times greater than AC algorithm that not adopt loop unrolling. The performance improvements using loop unrolling are 1.1, 0.2, and 1.5 times greater than those using global id, local id, and local memory optimizations mentioned above.

An Efficient Service Function Chains Orchestration Algorithm for Mobile Edge Computing

  • Wang, Xiulei;Xu, Bo;Jin, Fenglin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.12
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    • pp.4364-4384
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    • 2021
  • The dynamic network state and the mobility of the terminals make the service function chain (SFC) orchestration mechanisms based on static and deterministic assumptions hard to be applied in SDN/NFV mobile edge computing networks. Designing dynamic and online SFC orchestration mechanism can greatly improve the execution efficiency of compute-intensive and resource-hungry applications in mobile edge computing networks. In order to increase the overall profit of service provider and reduce the resource cost, the system running time is divided into a sequence of time slots and a dynamic orchestration scheme based on an improved column generation algorithm is proposed in each slot. Firstly, the SFC dynamic orchestration problem is formulated as an integer linear programming (ILP) model based on layered graph. Then, in order to reduce the computation costs, a column generation model is used to simplify the ILP model. Finally, a two-stage heuristic algorithm based on greedy strategy is proposed. Four metrics are defined and the performance of the proposed algorithm is evaluated based on simulation. The results show that our proposal significantly provides more than 30% reduction of run time and about 12% improvement in service deployment success ratio compared to the Viterbi algorithm based mechanism.

An Efficient Encryption Technique for Cloud-Computing in Mobile Environments (모바일환경에서 클라우드 컴퓨팅 보안을 위한 효율적인 암호화기술)

  • Hwang, Jae-Young;Choi, Dong-Wook;Chung, Yeon-Ho
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.4
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    • pp.298-302
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    • 2011
  • In this paper, we propose an efficient encryption algorithm for ensuring data privacy and security for cloud computing in mobile environments. As part of the evaluation of the proposed algorithm, we have implemented the algorithm in a PC environment and compared with the well-known encryption algorithm of the Data Encryption Standard (DES). The conventional DES algorithm is hard to maintain privacy, due to the fact that its initial and final permutation are known to the network To prevent this critical weakness, a triple DES algorithm has been reported, but it has a disadvantage of long encryption time. In this study, we propose random interleaving algorithm that uses the permutation table for improving privacy further. The proposed algorithm is found to run faster than the triple DES algorithm and also offers improved security in a wireless communication system.

Minimizing Energy Consumption in Scheduling of Dependent Tasks using Genetic Algorithm in Computational Grid

  • Kaiwartya, Omprakash;Prakash, Shiv;Abdullah, Abdul Hanan;Hassan, Ahmed Nazar
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.8
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    • pp.2821-2839
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    • 2015
  • Energy consumption by large computing systems has become an important research theme not only because the sources of energy are depleting fast but also due to the environmental concern. Computational grid is a huge distributed computing platform for the applications that require high end computing resources and consume enormous energy to facilitate execution of jobs. The organizations which are offering services for high end computation, are more cautious about energy consumption and taking utmost steps for saving energy. Therefore, this paper proposes a scheduling technique for Minimizing Energy consumption using Adapted Genetic Algorithm (MiE-AGA) for dependent tasks in Computational Grid (CG). In MiE-AGA, fitness function formulation for energy consumption has been mathematically formulated. An adapted genetic algorithm has been developed for minimizing energy consumption with appropriate modifications in each components of original genetic algorithm such as representation of chromosome, crossover, mutation and inversion operations. Pseudo code for MiE-AGA and its components has been developed with appropriate examples. MiE-AGA is simulated using Java based programs integrated with GridSim. Analysis of simulation results in terms of energy consumption, makespan and average utilization of resources clearly reveals that MiE-AGA effectively optimizes energy, makespan and average utilization of resources in CG. Comparative analysis of the optimization performance between MiE-AGA and the state-of-the-arts algorithms: EAMM, HEFT, Min-Min and Max-Min shows the effectiveness of the model.

Code Optimization in DNA Computing for the Hamiltonian Path Problem (해밀톤 경로 문제를 위한 DNA 컴퓨팅에서 코드 최적화)

  • 김은경;이상용
    • Journal of KIISE:Software and Applications
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    • v.31 no.4
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    • pp.387-393
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    • 2004
  • DNA computing is technology that applies immense parallel castle of living body molecules into information processing technology, and has used to solve NP-complete problems. However, there are problems which do not look for solutions and take much time when only DNA computing technology solves NP-complete problems. In this paper we proposed an algorithm called ACO(Algorithm for Code Optimization) that can efficiently express DNA sequence and create good codes through composition and separation processes as many as the numbers of reaction by DNA coding method. Also, we applied ACO to Hamiltonian path problem of NP-complete problems. As a result, ACO could express DNA codes of variable lengths more efficiently than Adleman's DNA computing algorithm could. In addition, compared to Adleman's DNA computing algorithm, ACO could reduce search time and biological error rate by 50% and could search for accurate paths in a short time.

Interaction Logic and Algorithm in Smart Cloud Computing (스마트 클라우드 컴퓨팅의 상호작용 로직 및 알고리즘)

  • Lee, Tae-Gyu;Shin, Seong-Yoon;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.203-206
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    • 2014
  • This paper discuss both cloud computing and smart computing, and then debates structural and functional issues about how the two computing systems interact for offering user-friendly information solutions. Smart Table is proposed to configure cloud resources. Smart Control algorithm is proposed to choose the best resources. The information interaction between cloud computing and smart computing services is realized for efficient construction of information systems and for user's convenience of information services.

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Fully Verifiable Algorithm for Secure Outsourcing of Bilinear Pairing in Cloud Computing

  • Dong, Min;Ren, Yanli;Zhang, Xinpeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.7
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    • pp.3648-3663
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    • 2017
  • With the development of cloud computing and widespread availability of mobile devices, outsourcing computation has gotten more and more attention in cloud computing services. The computation of bilinear pairing is the most expensive operation in pair-based cryptographic schemes. Currently, most of the algorithms for outsourcing bilinear pairing have small checkability or the outsourcers need to operate expensive computations. In this paper, we propose an efficient algorithm for outsourcing bilinear pairing with two servers, where the outsourcers can detect the errors with a probability of 1 if the cloud servers are dishonest, and the outsourcers are not involved in any complex computations. Finally, the performance evaluation demonstrates that the proposed algorithm is most efficient in all of fully verifiable outsourcing algorithms for bilinear pairing.

Combined Service Subscription and Delivery Energy-Efficient Scheduling in Mobile Cloud Computing

  • Liu, Xing;Yuan, Chaowei;Peng, Enda;Yang, Zhen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.5
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    • pp.1587-1605
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    • 2015
  • Mobile cloud computing (MCC) combines mobile Internet and cloud computing to improve the performance of applications. In MCC, the data processing and storage for mobile devices (MDs) is provided on the remote cloud. However, MCC faces the problem of energy efficiency caused by randomly varying channels. In this paper, by introducing the Lyapunov optimization method, we propose a combined service subscription and delivery (CSSD) algorithm that can guide the users to subscribe to services reasonably. This algorithm can also determine whether to deliver the data and to whom data is sent in the current time unit based on the queue backlog and the channel state. Numerical results validate the correctness and effectiveness of our proposed CSSD algorithm.

QPlayer: Lightweight, scalable, and fast quantum simulator

  • Ki-Sung Jin;Gyu-Il Cha
    • ETRI Journal
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    • v.45 no.2
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    • pp.304-317
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    • 2023
  • With the rapid evolution of quantum computing, digital quantum simulations are essential for quantum algorithm verification, quantum error analysis, and new quantum applications. However, the exponential increase in memory overhead and operation time is challenging issues that have not been solved for years. We propose a novel approach that provides more qubits and faster quantum operations with smaller memory than before. Our method selectively tracks realized quantum states using a reduced quantum state representation scheme instead of loading the entire quantum states into memory. This method dramatically reduces memory space ensuring fast quantum computations without compromising the global quantum states. Furthermore, our empirical evaluation reveals that our proposed idea outperforms traditional methods for various algorithms. We verified that the Grover algorithm supports up to 55 qubits and the surface code algorithm supports up to 85 qubits in 512 GB memory on a single computational node, which is against the previous studies that support only between 35 qubits and 49 qubits.

Modified SPaC Algorithm Using the Community Computing Network in huge area Community Computing Environment (광범위 Community Computing 환경에서의 Community Computing Network를 이용한 수정된 패킷 결합 알고리즘)

  • Song, Jwa-Hee;Choi, Jung-Dae;Chang, Hoon;Kim, Seok-Yoon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2008.06a
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    • pp.163-167
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    • 2008
  • 본 논문에서는 광범위 Community Computing 환경에서의 Community Computing Network의 에너지 효율과 신뢰성을 높이기 위한 수정된 SPaC(Simple Packet Combining)를 제안한다. 제안하는 수정된 SPaC는 같은 패킷을 두 개 이상의 오류가 있는 패킷을 이용하여 에러를 복구하는 기존의 SPaC를 수정하여 특정 threshold 값을 사용하여 감청 시 CPU의 처리량을 줄이고 패리티 패킷을 이용하여 높은 신뢰성과 보다 향상된 에너지 효율을 가진다.

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