• Korean Management Science Review
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• v.14 no.2
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• pp.47-61
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• 1997

This paper considers the parallel machines scheduling problem characterized as a multi-objective combinatorial problem. As this problem belongs to the NP-complete problem, genetic algorithms are applied instead of the traditional analytical approach. The purpose of this study is to show how the problem can be effectively solved by using genetic algorithms with a permutation approach. First, a permutation representation which can effectively represent the chromosome is introduced for this problem . Next, a schedule builder which employs the combination of scheduling theories and a simple heuristic approach is suggested. Finally, through the computer experiments of genetic algorithm to test problems, we show that the niche formation method does not contribute to getting better solutions and that the PMX crossover operator is the best among the selected four recombination operators at least for our problem in terms of both the performance of the solution and the operational convenience.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.4
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• pp.21-29
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• 2003

The traffic scheduling problem for a satellite cluster with an arbitrary number of satellites is considered. which is one of the most interesting problems in the satellite communication scheduling area. This problem is to find a time slot assignment maximizing the transponder utilization for a satellite cluster This problem is known to be NP-complete, and several heuristic algorithms have been proposed. In this paper, we suggest new efficient algorithms for this problem, which have less time complexity than the best existing one and provide much better solution quality. Extensive simulation results are reported.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5780-5802
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• 2017

Cloud computing system consists of distributed resources in a dynamic and decentralized environment. Therefore, using cloud computing resources efficiently and getting the maximum profits are still challenging problems to the cloud service providers and cloud service users. It is important to provide the efficient scheduling. To schedule cloud resources, numerous heuristic algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Cuckoo Search (CS) algorithms have been adopted. The paper proposes a Modified Particle Swarm Optimization (MPSO) algorithm to solve the above mentioned issues. We first formulate an optimization problem and propose a Modified PSO optimization technique. The performance of MPSO was evaluated against PSO, and GA. Our experimental results show that the proposed MPSO minimizes the task execution time, and maximizes the resource utilization rate.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.47-47
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• 1989

This paper considers the parallel machines scheduling problem characterized as a multi-objective combinatorial problem. As this problem belongs to the NP-complete problem, genetic algorithms are applied instead of the traditional analytical approach. The purpose of this study is to show how the problem can be effectively solved by using genetic algorithms with a permutation approach. First, a permutation representation which can effectively represent the chromosome is introduced for this problem . Next, a schedule builder which employs the combination of scheduling theories and a simple heuristic approach is suggested. Finally, through the computer experiments of genetic algorithm to test problems, we show that the niche formation method does not contribute to getting better solutions and that the PMX crossover operator is the best among the selected four recombination operators at least for our problem in terms of both the performance of the solution and the operational convenience.

• Journal of Navigation and Port Research
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• v.28 no.4
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• pp.299-303
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• 2004

In the Internet, to guarantee transmission rate and delay and to achieve fair bandwidth allocation, many per-flow scheduling algorithms, such as fair queueing, which have many desirable properties for congestion control, have been proposed and designed. However, algorithms based on per-flow need maintain rate state, buffer management and packet scheduling, so that it cost great deal ： implement. Therefore, in this paper, to implement routers cost-effectively, we propose CS-FNE algorithm based on FNE in Core-Stateless network We evaluate CS-FNE comparing with four additional algorithms i.e., CSFQ, FRED, RED and DRR, in several different, configurations and traffic sources. Through simulation results, we show that CS-FNE algorithm can allocate fair bandwidth approximately and is simpler and easier to implement than other per-flow basis queueing mechanisms.

• Management Science and Financial Engineering
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• v.16 no.1
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• pp.59-79
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• 2010

This paper considers bandwidth allocation and scheduling problems on Ethernet Passive Optical Networks (EPON). EPON is one of the good candidates for the optical access network. This paper formulates the bandwidth allocation problem as a nonlinear mathematical one and characterizes the optimal bandwidth allocation which maximizes weighted sum of throughput and fairness. Based upon the characterization, two heuristic algorithms are suggested with various numerical tests. The test results show that our algorithms can be used for efficient bandwidth allocation on the EPON. This paper also shows that the WSPT (Weighted Shortest Processing Time) rule is optimal for minimization the total delay time in transmitting the traffic of the given allocated bandwidth.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.471-474
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• 2011

In parallel job scheduling, each job can be executed simultaneously on multiple machines at a time. Thus in the input instance, a job $J_i$ requires the number $m_i$ of machines on which it shall be processed. The algorithm should determine not only the execution order of jobs but also the machines on which the jobs are executed. In this paper, when the jobs have deadlines, the problem is to maximize the total work of jobs which is completed by their deadlines. The problem is known to be strongly NP-hard [5] and we investigate the approximation algorithms for the problem. We consider a model in which the algorithm can have more machines than the adversary. With this advantage, the problem is how good solution the algorithm can produce against the optimal algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.8-18
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• 2009

CableLAB published DOCSIS 3.0 Specifications to supply broadband access to homes and small businesses. The primary technique of DOCSIS 3.0 Specification is channel bonding which provides cable operators with a flexible way to significantly increase up/downstream speeds. In this paper, we propose the upstream scheduler that serves channel bonding. Proposed scheduler consists of two sub-scheduler: bonding group scheduler and channel scheduler. Also, we propose three scheduling algorithms to allocate request bandwidth of CM to each bonding channel: equivalent scheduling algorithm, current request-based scheduling algorithm, and last grant-based scheduling algorithm. In order to evaluate the performance of these algorithms and DOCSIS 3.0 MAC protocol, we develop the DOCSIS 3.0 simulator with the network simulator, OPNET, to model DOCSIS network, CMTS, and CM. Our results show that equivalent scheduling algorithm is superior to others in the view of transmission delay and throughput and DOCSIS 3.0 protocol provides higher throughput than pre-DOCSIS 3.0 protocol.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.44-56
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• 2009

Multimedia streaming service is susceptible to loss and delay of data as it requires high bandwidth and real time processing. Therefore QoS cannot be guaranteed due to data loss caused by heavy network traffic and error of wireless channel. To solve these problems, studies about algorithms which improve the quality of multimedia by serving differently according to the priority of packets in multimedia stream. Two algorithms are proposed in this paper. The first algorithm proposed is WMS-1(Wireless Multimedia Scheduling-1) algorithm which acts like IWFQ when any wireless loss is occurred but assigns channels first in case of urgent situation like when the running time of multimedia runs out. The second algorithm proposed is WMS-2(Wireless Multimedia Scheduling-2) algerithm that assigns priority to multimedia flow and schedules flow that has higher priority according to type of frame first. The comparison with other existing scheduling algorithms shows that multimedia service quality of the proposed algorithm is improved and the larger the queue size of base station is, the better total quality of service and fairness were gained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1544-1572
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• 2011

Task placement and scheduling are traditionally studied in following aspects: resource utilization, application throughput, application execution latency and starvation, and recently, the studies are more on application scalability and application performance. A methodology for task placement and scheduling centered on tasks based on virtual machines is studied in this paper to improve the performances of systems and dynamic adaptability in applications development and deployment oriented parallel computing. For parallel applications with no real-time constraints, we describe a thought of feature model and make a formal description for four layers of task placement and scheduling. To place the tasks to different layers of virtual computing systems, we take the performances of four layers as the goal function in the model of task placement and scheduling. Furthermore, we take the personal preference, the application scalability for a designer in his (her) development and deployment, as the constraint of this model. The workflow of task placement and scheduling based on virtual machines has been discussed. Then, an algorithm TPVM is designed to work out the optimal scheme of the model, and an algorithm TEVM completes the execution of tasks in four layers. The experiments have been performed to validate the effectiveness of time estimated method and the feasibility and rationality of algorithms. It is seen from the experiments that our algorithms are better than other four algorithms in performance. The results show that the methodology presented in this paper has guiding significance to improve the efficiency of virtual computing systems.