• Title/Summary/Keyword: Key scheduling algorithm

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Differential Evolution Algorithm for Job Shop Scheduling Problem

  • Wisittipanich, Warisa;Kachitvichyanukul, Voratas
    • Industrial Engineering and Management Systems
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    • v.10 no.3
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    • pp.203-208
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    • 2011
  • Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

Conflict Graph-based Downlink Resource Allocation and Scheduling for Indoor Visible Light Communications

  • Liu, Huanlin;Dai, Hongyue;Chen, Yong;Xia, Peijie
    • Journal of the Optical Society of Korea
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    • v.20 no.1
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    • pp.36-41
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    • 2016
  • Visible Light Communication (VLC) using Light Emitting Diodes (LEDs) within the existing lighting infrastructure can reduce the implementation cost and may gain higher throughput than radio frequency (RF) or Infrared (IR) based wireless systems. Current indoor VLC systems may suffer from poor downlink resource allocation problems and small system throughput. To address these two issues, we propose an algorithm called a conflict graph scheduling (CGS) algorithm, including a conflict graph and a scheme that is based on the conflict graph. The conflict graph can ensure that users are able to transmit data without interference. The scheme considers the user fairness and system throughput, so that they both can get optimum values. Simulation results show that the proposed algorithm can guarantee significant improvement of system throughput under the premise of fairness.

Enhanced Technique for Performance in Real Time Systems (실시간 시스템에서 성능 향상 기법)

  • Kim, Myung Jun
    • Journal of Information Technology Services
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    • v.16 no.3
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    • pp.103-111
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    • 2017
  • The real time scheduling is a key research area in high performance computing and has been a source of challenging problems. A periodic task is an infinite sequence of task instance where each job of a task comes in a regular period. The RMS (Rate Monotonic Scheduling) algorithm has the advantage of a strong theoretical foundation and holds out the promise of reducing the need for exhaustive testing of the scheduling. Many real-time systems built in the past based their scheduling on the Cyclic Executive Model because it produces predictable schedules which facilitate exhaustive testing. In this work we propose hybrid scheduling method which combines features of both of these scheduling algorithms. The original rate monotonic scheduling algorithm didn't consider the uniform sampling tasks in the real time systems. We have enumerated some issues when the RMS is applied to our hybrid scheduling method. We found the scheduling bound for the hard real-time systems which include the uniform sampling tasks. The suggested hybrid scheduling algorithm turns out to have some advantages from the point of view of the real time system designer, and is particularly useful in the context of large critical systems. Our algorithm can be useful for real time system designer who must guarantee the hard real time tasks.

APPLYING ELITIST GENETIC ALGORITHM TO RESOURCE-CONSTRAINED PROJECT SCHEDULING PROBLEM

  • Jin-Lee Kim;Ok-Kyue Kim
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.739-748
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    • 2007
  • The objective of this research study is to develop the permutation-based genetic algorithm for solving the resource-constrained project scheduling problem in construction engineering by incorporating elitism into genetic algorithm. A key aspect of the algorithm was the development of the elitist roulette selection operator to preserve the best individual solution for the next generation so the improved solution can be obtained. Another notable characteristic is the application of the parallel schedule generation scheme to generate a feasible solution to the problem. Case studies with a standard test problem were presented to demonstrate the performance and accuracy of the algorithm. The computational results indicate that the proposed algorithm produces reasonably good solutions for the resource-constrained project scheduling problem.

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A LEA Implementation study on UICC-16bit (UICC 16bit 상에서의 LEA 구현 적합성 연구)

  • Kim, Hyun-Il;Park, Cheolhee;Hong, Dowon;Seo, Changho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.24 no.4
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    • pp.585-592
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    • 2014
  • In this paper, we study the LEA[1] block cipher system in UICC-16bit only. Also, we explain a key-schedule function and encryption/decryption structures, propose an advanced modified key-scheduling, and perform LEA in UICC-16bit that we proposed advanced modified key-scheduling. Also, we compare LEA with ARIA that proposed domestic standard block cipher, and we evaluate the efficiency on the LEA algorithm.

Task Scheduling Algorithm in Multiprocessor System Using Genetic Algorithm (유전 알고리즘을 이용한 멀티프로세서 시스템에서의 태스크 스케쥴링 알고리즘)

  • Kim Hyun-Chul
    • Journal of Korea Multimedia Society
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    • v.9 no.1
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    • pp.119-126
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    • 2006
  • The task scheduling in multiprocessor system is one of the key elements in the effective utilization of multiprocessor systems. The optimal assignment of tasks to multiprocessor is, in almost practical cases, an NP-hard problem. Consequently algorithms based on various modern heuristics have been proposed for practical reason. This paper proposes a new task scheduling algorithm using Genetic Algorithm which combines simulated annealing (GA+SA) in multiprocessor environment. In solution algorithms, the Genetic Algorithm (GA) and the simulated annealing (SA) are cooperatively used. In this method, the convergence of GA is improved by introducing the probability of SA as the criterion for acceptance of new trial solution. The objective of proposed scheduling algorithm is to minimize makespan. The effectiveness of the proposed algorithm is shown through simulation studies. In simulation studies, the result of proposed algorithm is better than that of any other algorithms.

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MOPSO-based Data Scheduling Scheme for P2P Streaming Systems

  • Liu, Pingshan;Fan, Yaqing;Xiong, Xiaoyi;Wen, Yimin;Lu, Dianjie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.10
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    • pp.5013-5034
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    • 2019
  • In the Peer-to-Peer (P2P) streaming systems, peers randomly form a network overlay to share video resources with a data scheduling scheme. A data scheduling scheme can have a great impact on system performance, which should achieve two optimal objectives at the same time ideally. The two optimization objectives are to improve the perceived video quality and maximize the network throughput, respectively. Maximizing network throughput means improving the utilization of peer's upload bandwidth. However, maximizing network throughput will result in a reduction in the perceived video quality, and vice versa. Therefore, to achieve the above two objects simultaneously, we proposed a new data scheduling scheme based on multi-objective particle swarm optimization data scheduling scheme, called MOPSO-DS scheme. To design the MOPSO-DS scheme, we first formulated the data scheduling optimization problem as a multi-objective optimization problem. Then, a multi-objective particle swarm optimization algorithm is proposed by encoding the neighbors of peers as the position vector of the particles. Through extensive simulations, we demonstrated the MOPSO-DS scheme could improve the system performance effectively.

An Implementation of YK2 Cipher System for Electronic Commerce Security (전자상거래 보안을 위한 YK2 암호시스템의 구현)

  • 서장원
    • The Journal of Society for e-Business Studies
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    • v.6 no.1
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    • pp.17-33
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    • 2001
  • EC(Electronic Commerce) which is done on the virtual space through Internet has strong point like independence from time and space. On the contrary, it also has weak point like security problem because anybody can access easily to the system due to open network attribute of Internet, Therefore, we need the solutions that protect the EC security problem for safe and useful EC activity. One of these solutions is the implementation of strong cipher system. YK2(Young Ku King) cipher system proposed in this paper is good solution for the EC security and it overcome the limit of current block cipher system using 128 bits key length for input, output, encryption key and 32 rounds. Moreover, it is designed for the increase of time complexity by adapting more complex design for key scheduling algorithm regarded as one of important element effected to encryption.

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A Scheduling Algorithm for Continuous Media (연속미디어를 위한 스케쥴링 알고리즘)

  • 유명련;안병철
    • Journal of Korea Multimedia Society
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    • v.4 no.5
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    • pp.371-376
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    • 2001
  • Since continuous media such as video and audio data are displayed within a certain time constraint, their computation and manipulation should be handled under limited condition. Traditional real-time scheduling algorithms cold be directly applicable, because they are not suitable for multimedia scheduling applications which support many clients at the same time. Rate Regulating Proportional Share Scheduling Algorithm based on the stride scheduler is a scheduling algorithm considered the time constraint of the continuous media. The stride schedulers, which are designed to general tasks, guarantee the fairness of resource allocation and predictability. The key concept of RRPSSA is a rate regulator which prevents tasks from receiving more resource than its share in a given period. But this algorithm loses fairness which is a strong point of the stride schedulers, and does not show graceful degradation of performance under overloaded situation. This paper proposes a new modified algorithm, namely Modified Proportional Share Scheduling Algorithm considering the characteristics of multimedia data such as its continuity and time dependency. Proposed scheduling algorithm shows graceful degradation of performance in overloaded situation and it reduces the scheduling violations up to 70% by maintaining the fair resource allocation. The number of context switching is 8% less than RRPSSA and the overall performance is increased.

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Design of Optimized ARIA Crypto-Processor Using Composite Field S-Box (합성체 S-Box 기반 최적의 ARIA 암호프로세서 설계)

  • Kang, Min Sup
    • KIPS Transactions on Computer and Communication Systems
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    • v.8 no.11
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    • pp.271-276
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    • 2019
  • Conventional ARIA algorithm which is used LUT based-S-Box is fast the processing speed. However, the algorithm is hard to applied to small portable devices. This paper proposes the hardware design of optimized ARIA crypto-processor based on the modified composite field S-Box in order to decrease its hardware area. The Key scheduling in ARIA algorithm, both diffusion and substitution layers are repeatedly used in each round function. In this approach, an advanced key scheduling method is also presented of which two functions are merged into only one function for reducing hardware overhead in scheduling process. The designed ARIA crypto-processor is described in Verilog-HDL, and then a logic synthesis is also performed by using Xilinx ISE 14.7 tool with target the Xilnx FPGA XC3S1500 device. In order to verify the function of the crypto-processor, both logic and timing simulation are also performed by using simulator called ModelSim 10.4a.