• Title/Summary/Keyword: Optimal computation

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A Cloud-Edge Collaborative Computing Task Scheduling and Resource Allocation Algorithm for Energy Internet Environment

  • Song, Xin;Wang, Yue;Xie, Zhigang;Xia, Lin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.6
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    • pp.2282-2303
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    • 2021
  • To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

Optimal Control of Nonlinear Systems Using Block Pulse Functions (블럭펄스 함수를 이용한 비선형 시스템의 최적제어)

  • Jo, Yeong-Ho;An, Du-Su
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.3
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    • pp.111-116
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    • 2000
  • In this paper, we presented a new algebraic iterative algorithm for the optimal control of the nonlinear systems. The algorithm is based on tow steps. The first step transforms optimal control problem into a sequence of linear optimal control problem using the quasilinearization method. In the second step, TPB(two point boundary condition problem) is solved by algebraic equations instead of differential equations using BPF(block pulse functions). The proposed algorithm is simple and efficient in computation for the optimal control of nonlinear systems. In computer simulation, the algorithm was verified through the optimal control design of Van del pole system and Volterra Predatory-prey system.

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Optimization of Generator Maintenance Scheduling with Consideration on the Equivalent Operation Hours

  • Han, Sangheon;Kim, Hyoungtae;Lee, Sungwoo;Kim, Wook
    • Journal of Electrical Engineering and Technology
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    • v.11 no.2
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    • pp.338-346
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    • 2016
  • In order for the optimal solution of generators’ annual maintenance scheduling to be applicable to the actual power system it is crucial to incorporate the constraints related to the equivalent operation hours (EOHs) in the optimization model. However, most of the existing researches on the optimal maintenance scheduling are based on the assumption that the maintenances are to be performed periodically regardless of the operation hours. It is mainly because the computation time to calculate EOHs increases exponentially as the number of generators becomes larger. In this paper an efficient algorithm based on demand grouping method is proposed to calculate the approximate EOHs in an acceptable computation time. The method to calculate the approximate EOHs is incorporated into the optimization model for the maintenance scheduling with consideration on the EOHs of generators. The proposed method is successfully applied to the actual Korean power system and shows significant improvement when compared to the result of the maintenance scheduling algorithm without consideration on EOHs.

An Optimal Parallel Algorithm for Generating Computation Tree Form on Linear Array with Slotted Optical Buses (LASOB 상에서 계산 트리 형식을 생성하기 위한 최적 병렬 알고리즘)

  • Kim, Young-Hak
    • Journal of KIISE:Computer Systems and Theory
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    • v.27 no.5
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    • pp.475-484
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    • 2000
  • Recently, processor arrays to enhance the banRecently, processor arrays to enhance the bandwidth of buses and to reduce the complexity of hardwares, using optical buses instead of electronic buses, have been proposed in manyliteratures. In this paper, we first propose a constant-time algorithm for parentheses matching problemon a linear array with slotted optical buses (LASOB).Then, given an algebraic expression of length n, we also propose a cost optimal parallel algorithmthat constructs computational tree form in the steps of constant time on LASOB with n processorsby using parentheses matching algorithm. A cost optimal parallel algorithm for this problem that runsin constant time has not yet been known on any parallel computation models.

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Design of Ternary Logic Circuits Based on Reed-Muller Expansions (Reed-Muller 전개식에 의한 3치 논리회로의 설계)

  • Seong, Hyeon-Kyeong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.3
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    • pp.491-499
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    • 2007
  • In this paper, we present a design method of the ternary logic circuits based on Reed-Muller expansions. The design method of the presented ternary logic circuits checks the degree of each variable for the coefficients of Reed-Holler Expansions(RME) and determines the order of optimal control input variables that minimize the number of Reed-Muller Expansions modules. The order of optimal control input variables is utilized the computation of circuit cost matrix. The ternary logic circuits of the minimized tree structures to be constructed by RME modules based on Reed-Muller Expansions are realized using the computation results of its circuit cost matrix. This method is only performed under unit time in order to search for the optimal control input variables. Also, this method is able to be programmed by computer and the run time on programming is $3^n$.

Optimal Control of Nonlinear Systems Using The New Integral Operational Matrix of Block Pulse Functions (새로운 블럭펄스 적분연산행렬을 이용한 비선형계 최적제어)

  • Cho Young-ho;Shim Jae-sun
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.4
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    • pp.198-204
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    • 2003
  • In this paper, we presented a new algebraic iterative algorithm for the optimal control of the nonlinear systems. The algorithm is based on two steps. The first step transforms nonlinear optimal control problem into a sequence of linear optimal control problem using the quasilinearization method. In the second step, TPBCP(two point boundary condition problem) is solved by algebraic equations instead of differential equations using the new integral operational matrix of BPF(block pulse functions). The proposed algorithm is simple and efficient in computation for the optimal control of nonlinear systems and is less error value than that by the conventional matrix. In computer simulation, the algorithm was verified through the optimal control design of synchronous machine connected to an infinite bus.

Self-tuning optimal control of an active suspension using a neural network

  • Lee, Byung-Yun;Kim, Wan-Il;Won, Sangchul
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.295-298
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    • 1996
  • In this paper, a self-tuning optimal control algorithm is proposed to retain the optimal performance of an active suspension system, when the vehicle has some time varying parameters and parameter uncertainties. We consider a 2 DOF time-varying quarter car model which has the parameter variation of sprung mass, suspension spring constant and suspension damping constant. Instead of solving algebraic riccati equation on line, we propose a neural network approach as an alternative. The optimal feedback gains obtained from the off line computation, according to parameter variations, are used as the neural network training data. When the active suspension system is on, the parameters are identified by the recursive least square method and the trained neural network controller designer finds the proper optimal feedback gains. The simulation results are represented and discussed.

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Design of Optimal Controller for the Congestion in ATM Networks (ATM망의 체증을 해결하기 위한 최적 제어기 설계)

  • Jung Woo-Chae;Kim Young-Joong;Lim Myo-Taeg
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.6
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    • pp.359-365
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    • 2005
  • This paper presents an reduced-order near-optimal controller for the congestion control of Available Bit Rate (ABR) service in Asynchronous Transfer Mode (ATM) networks. We introduce the model, of a class of ABR traffic, that can be controlled using a Explicit Rate feedback for congestion control in ATM networks. Since there are great computational complexities in the class of optimal control problem for the ABR model, the near-optimal controller via reduced-order technique is applied to this model. It is implemented by the help of weakly coupling and singular perturbation theory, and we use bilinear transformation because of its computational convenience. Since the bilinear transformation can convert discrete Riccati equation into continuous Riccati equation, the design problems of optimal congestion control can be reduced. Using weakly coupling and singular perturbation theory, the computation time of Riccati equations can be saved, moreover the real-time congestion control for ATM networks can be possible.

An Optimal Circuit Structure for Implementing SEED Cipher Algorithm with Verilog HDL (SEED 암호알고리즘의 Verilog HDL 구현을 위한 최적화 회로구조)

  • Lee, Haeng Woo
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.1
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    • pp.107-115
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    • 2012
  • This paper proposes on the structure for reducing the circuit area and increasing the computation speed in implementing to hardware using the SEED algorithm of a 128-bit block cipher. SEED cipher can be implemented with S/W or H/W method. It should be important that we have minimize the area and computation time in H/W implementation. To increase the computation speed, we used the structure of the pipelined systolic array, and this structure is a simple thing without including any buffer at the input and output circuit. This circuit can record the encryption rate of 320 Mbps at 10 MHz clock. We have designed the circuit with the Verilog HDL coding showing the circuit performances in the figures and the table.

Sensitivity Analysis Using a Symbolic Computation Technique and Optimal Design of Suspension Hard Points (기호계산을 이용한 현가장치의 민감도 해석 및 설계점의 최적 설계)

  • Chun, Hung-Ho;Tak, Tae-Oh
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.4 s.97
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    • pp.26-36
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    • 1999
  • A general procedure for determining the optimum location of suspension hard points with respect to kinematic design parametes is presented. Suspensions are modeled as connection of rigid bodies by ideal kinematic joints. Constraint equations of the kinematic joints are expressed in terms of the generalized coordinates and hard points. By directly differentiating the constraint equations with respect to the hard points, kinematic sencitivity equations are obtained. In order to cope with algebraic complexity associated with the differentiation process, a symbolic computation technique is used. A performance index is defined in terms of static design parameters such as camber, caster, toe, ect.. Gradient of the performance index can be analytically computed from the kinematic sensitivity equations. Optimization results show the effectiveness and validity of the procedure, which is applicable to any type of suspension if its kinematic configurations are given.

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