• 제목/요약/키워드: Computation cost

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Strategy for Task Offloading of Multi-user and Multi-server Based on Cost Optimization in Mobile Edge Computing Environment

  • He, Yanfei;Tang, Zhenhua
    • Journal of Information Processing Systems
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    • 제17권3호
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    • pp.615-629
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    • 2021
  • With the development of mobile edge computing, how to utilize the computing power of edge computing to effectively and efficiently offload data and to compute offloading is of great research value. This paper studies the computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in order to minimize system energy consumption, the problem is modeled by considering the joint optimization of the offloading strategy and the wireless and computing resource allocation in a multi-user and multi-server scenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. As the centralized optimization method is an NP problem, the game method is used to achieve effective computation offloading in a distributed manner. The decision problem of distributed computation offloading between the mobile equipment is modeled as a multi-user computation offloading game. There is a Nash equilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose a distributed computation offloading algorithm, which first calculates offloading weights, and then distributedly iterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified by simulation experiments. Simulation results show that our proposed algorithm can achieve the balance by a limited number of iterations. At the same time, the algorithm outperforms several other advanced computation offloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.

모바일 클라우드 컴퓨팅에서 모바일 기기의 에너지 절약을 위한 함수 수준 정적 오프로딩 기법 (A Function Level Static Offloading Scheme for Saving Energy of Mobile Devices in Mobile Cloud Computing)

  • 민홍;정진만;허준영
    • 정보과학회 논문지
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    • 제42권6호
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    • pp.707-712
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    • 2015
  • 모바일 클라우드 컴퓨팅은 모바일 기기의 자원제약적인 한계를 극복하기 위해 클라우드 서비스를 활용하는 기술로 모바일 기기에서 실행해야 할 일부 작업을 클라우드에서 수행하게 하는 컴퓨테이션 오프로딩 기법이 사용된다. 오프로딩에 필요한 통신 비용보다 모바일 기기 내에서의 연산 비용이 클 경우 모바일 기기는 클라우드에게 작업 수행을 위탁한다. 모바일 기기에서 수행할 작업과 클라우드에서 수행할 작업을 분할하기 위한 기존의 비용 분석 모델은 함수 호출에 필요한 데이터 전송과 응답 시간만을 오프로딩 비용으로 산정하였다. 본 논문에서는 컴퓨테이션 오프로딩 비용 산출 시 함수의 호출 및 응용 프로그램의 동기화 빈도를 고려한 작업 분할 기법을 제안하였고 실험을 통해 기존의 기법들에 비해 에너지 효율성을 높일 수 있음을 확인하였다.

벡터양자화를 이용한 웨이브렛 영상데이터 압축 (Wavelet Image Data Compression Using Vector Quantization)

  • 최유일;조창호;이상효;조도현;이종용
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.2287-2290
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    • 2003
  • In this paper, an image vector quantization method is proposed not only to improve the compression ratio but also to reduce the computation cost. The proposed method could save the computation cost of codebook generation and encoding by using the modified LBG algorithm of Partial Search Partial Distortion (PSPD) in wavelet domain, by which the code book was constructed together with the partial codebook search, the partial code vector elements, and the interruption criterion. We have designed and implemented the vector quantizer to verify the improvement in reducing compression ratio in encoding processing and reducing the computation cost.

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Verifiable Outsourced Ciphertext-Policy Attribute-Based Encryption for Mobile Cloud Computing

  • Zhao, Zhiyuan;Wang, Jianhua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권6호
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    • pp.3254-3272
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    • 2017
  • With the development of wireless access technologies and the popularity of mobile intelligent terminals, cloud computing is expected to expand to mobile environments. Attribute-based encryption, widely applied in cloud computing, incurs massive computational cost during the encryption and decryption phases. The computational cost grows with the complexity of the access policy. This disadvantage becomes more serious for mobile devices because they have limited resources. To address this problem, we present an efficient verifiable outsourced scheme based on the bilinear group of prime order. The scheme is called the verifiable outsourced computation ciphertext-policy attribute-based encryption scheme (VOC-CP-ABE), and it provides a way to outsource intensive computing tasks during encryption and decryption phases to CSP without revealing the private information and leaves only marginal computation to the user. At the same time, the outsourced computation can be verified by two hash functions. Then, the formal security proofs of its (selective) CPA security and verifiability are provided. Finally, we discuss the performance of the proposed scheme with comparisons to several related works.

큐브 계산에서 I/O 비용을 줄이는 구간 기반 큐브 분할 (Range-based Cube Partitioning for Reducing I/O Cost in Cube Computation)

  • 박웅제;정연도;김진녕;이윤준;김명호
    • 한국정보과학회논문지:데이타베이스
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    • 제28권4호
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    • pp.596-605
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    • 2001
  • 본 논문은 OLAP에서의 I/O 비용을 줄이는 큐브 계산 방법으로, 구간 기반 큐브 분할 기법을 제안한다. 제안하는 방법은 큐브 분할 단계들 사이에 존재하는 계산의 일부를 중복시켜 처리하는 방법을 통해 큐브 분할 작업의 I/O 성능을 향상시킨다. 계산의 중복을 위하여 제안하는 방법은 애트리뷰트의 단 일 값이 아닌 애트리뷰트 값의 일정 구간을 기준으로 큐브를 분할한다 분석과 실험을 통하여 제안하는 방법의 성능을 기존 큐브 분할 방법과 비교하여 보인다.

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Cost-Aware Scheduling of Computation-Intensive Tasks on Multi-Core Server

  • Ding, Youwei;Liu, Liang;Hu, Kongfa;Dai, Caiyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권11호
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    • pp.5465-5480
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    • 2018
  • Energy-efficient task scheduling on multi-core server is a fundamental issue in green cloud computing. Multi-core processors are widely used in mobile devices, personal computers, and servers. Existing energy efficient task scheduling methods chiefly focus on reducing the energy consumption of the processor itself, and assume that the cores of the processor are controlled independently. However, the cores of some processors in the market are divided into several voltage islands, in each of which the cores must operate on the same status, and the cost of the server includes not only energy cost of the processor but also the energy of other components of the server and the cost of user waiting time. In this paper, we propose a cost-aware scheduling algorithm ICAS for computation intensive tasks on multi-core server. Tasks are first allocated to cores, and optimal frequency of each core is computed, and the frequency of each voltage island is finally determined. The experiments' results show the cost of ICAS is much lower than the existing method.

고차 발전 비용 함수를 고려한 새로운 경제급전 알고리즘 (A New Economic Dispatch Algorithm Considering Any Higher Order Generation Cost Functions)

  • 박정도;문영현
    • 대한전기학회논문지:전력기술부문A
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    • 제51권12호
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    • pp.603-610
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    • 2002
  • In this paper, a new economic dispatch algorithm for unit commitment is proposed to improve both the accuracy of the final solution and the calculation speed of economic dispatch. By using the inverse incremental cost functions, economic dispatch can be transformed into a simple optimization problem associated with an n-th order polynomial equation. The proposed method remarkably reduces the computation time with adaptability to any higher order generation cost functions. The proposed method is tested with sample system, which shows that the proposed algorithm yields more accurate and economical generation scheduling results with high computation speed.

모폴로지 연산에 사용되는 볼록 구조요소의 분해를 위한 알고리듬 (A Decomposition Algorithm for Convex Structuring Elements in Morphological Operation)

  • 온승엽
    • 한국시뮬레이션학회논문지
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    • 제13권1호
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    • pp.11-23
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    • 2004
  • The decomposition of a structuring element for a morphological operation reduces the amount of the computation required for executing the operation. In this paper, we present a new technique for the decomposition of convex structuring elements for morphological operations. We formulated the linear constraints for the decomposition of a convex polygon in discrete space, then the constraints are applied to the decomposition of a convex structuring element. Also, a cost function is introduced to represent the optimal criteria for decomposition. We use linear integer programming technique to find the combination of basis structuring elements which minimizes the amount of the computation required for executing the morphological operation. Formulating different cost functions for different implementation methods and computer architectures, we can determine the optimal decompositions which guarantee the minimal amounts of computation on different computing environment.

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페어링 및 ECC 상수배 연산의 계산 비용에 관하여 (On the Computational Cost of Pairing and ECC Scalar Multiplication)

  • 구남훈;조국화;김창훈;권순학
    • 한국통신학회논문지
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    • 제36권1C호
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    • pp.14-21
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    • 2011
  • 겹선형 페어링(bilinear pairing)을 기반으로 하는 암호 프로토콜들은 이산 대수 문제를 기반으로 하는 전통적인 타원 곡선 암호시스템을 대신하여 여러 방면에의 응용성을 제공한다. 겹선형 페어링의 빠른 계산을 위하여 최근 활발한 연구가 진행 중이지만, 여전히 ECC 상수배 연산에 비해서 페어링 연산에 사용되는 계산 비용은 상당히 크다고 여겨진다. 그러나 이진 유한체상의 페어링 계산 연구는 최근 많은 발전이 이루어졌다. 본 논문에서는 이진 유한체상에서의 BLS 서명스킴과 ECDSA 서명 스킴의 복잡도를 비교한다. 공정한 비교를 위하여 1024-bit RSA와 같은 레벨의 보안성을 가지는 160-bit ECDSA와 250-bit BLS를 선택하였다. 분석결과 BLS 스킴은 ECDSA에 비해 하드웨어 복잡도 및 계산 지연시간의 측면에서 많은 차이가 나지 않음을 설명해준다.

Optimal Decomposition of Convex Structuring Elements on a Hexagonal Grid

  • Ohn, Syng-Yup
    • The Journal of the Acoustical Society of Korea
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    • 제18권3E호
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    • pp.37-43
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    • 1999
  • In this paper, we present a new technique for the optimal local decomposition of convex structuring elements on a hexagonal grid, which are used as templates for morphological image processing. Each basis structuring element in a local decomposition is a local convex structuring element, which can be contained in hexagonal window centered at the origin. Generally, local decomposition of a structuring element results in great savings in the processing time for computing morphological operations. First, we define a convex structuring element on a hexagonal grid and formulate the necessary and sufficient conditions to decompose a convex structuring element into the set of basis convex structuring elements. Further, a cost function was defined to represent the amount of computation or execution time required for performing dilations on different computing environments and by different implementation methods. Then the decomposition condition and the cost function are applied to find the optimal local decomposition of convex structuring elements, which guarantees the minimal amount of computation for morphological operation. Simulation shows that optimal local decomposition results in great reduction in the amount of computation for morphological operations. Our technique is general and flexible since different cost functions could be used to achieve optimal local decomposition for different computing environments and implementation methods.

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