• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1882-1890
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• 2014

This paper proposes an augmented Lagrange Hopfield network (ALHN) based method for solving multi-objective short term fixed head hydrothermal scheduling problem. The main objective of the problem is to minimize both total power generation cost and emissions of $NO_x$, $SO_2$, and $CO_2$ over a scheduling period of one day while satisfying power balance, hydraulic, and generator operating limits constraints. The ALHN method is a combination of augmented Lagrange relaxation and continuous Hopfield neural network where the augmented Lagrange function is directly used as the energy function of the network. For implementation of the ALHN based method for solving the problem, ALHN is implemented for obtaining non-dominated solutions and fuzzy set theory is applied for obtaining the best compromise solution. The proposed method has been tested on different systems with different analyses and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is very efficient for solving the problem with good optimal solution and fast computational time. Therefore, the proposed ALHN can be a very favorable method for solving the multi-objective short term fixed head hydrothermal scheduling problems.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.2
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• pp.39-47
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• 2010

As vehicles become intelligent for convenience and safety of drivers, in-vehicle networking (IVN) systems are essential components of intelligent vehicles. Recently, the chassis networking system which require increased network capacity and real-time capability is being developed to expand the application area of IVN systems. Also, FlexRay has been developed for the chassis networking system. However, FlexRay needs a complex scheduling method of static segment, which is a barrier for implementing the chassis networking system. Especially, if we want to migrate from CAN network to FlexRay network using CAN message database that was well constructed for the chassis networking system by automotive vendors, a novel scheduling method is necessary to be able to reduce design complexity. This paper presents a node-based scheduling method for FlexRay network system. And, in order to demonstrate the method's feasibility, its performance is evaluated through an experimental testbed.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.51-61
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• 1999

A cell scheduling method of Queue for the ATM switch is proposed and simulated. In this paper, we present the cell scheduling method proper to the proposed queue and the improved queue with Queue Sharing(QS) structure for CBR, VBR, ABR traffic. The proposed QS structure minimizes the CLS(Cell Loss Ratio) of ABR traffic and decreases the CLR of bursty VBR traffic. Also we propose a cell scheduling method using VRR(Variable Round Robin) scheme proper to the high-speed(ATM) switch. The VRR scheme provides a fairness in terms of service chance for the queues in the ATM switch as well as QOS of their cell delay characteristic of CBR and VBR traffic, QOS of ABR CLR. The simulation results show the proposed method achieves excellent CLR and average cell delay performance for the various ATM traffic services in the Queue Sharing structure.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.1
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• pp.29-35
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• 2004

Locomotive scheduling in railway systems experiences many difficulties because of the complex interrelations among resources, knowledge and various constraints. Artificial intelligence technology has been applied to solve these scheduling problems. These technologies have proved to be efficient in representing knowledge and rules for complex scheduling problems. In this paper, we have applied the CSP (Constraints Satisfaction Problems) programming technique, one of the AI techniques, to solve the problems associated with locomotive scheduling. This method is more effective at solving complex scheduling problems than available mathematical programming techniques. The advanced locomotive scheduling system using the CSP programming technique is realized based on the actual timetable of the Saemaul type train on the Kyong-bu line. In this paper, an overview of the CSP programming technique is described, the modeling of domain and constraints is represented and the experimental results are compared with the real-world existing schedule. It is verified that the scheduling results by CSP programming are superior to existing scheduling performed by human experts. The executing time for locomotive scheduling is remarkably reduced to within several decade seconds, something requiring several days in the case of locomotive scheduling by human experts.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.399-406
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• 2023

Cloud computing has been evolved to support edge computing architecture that combines fog management layer with edge servers. The main reason why it is received much attention is low communication latency for real-time IoT applications. At the same time, various cloud task scheduling techniques based on artificial intelligence have been proposed. Artificial intelligence-based cloud task scheduling techniques show better performance in comparison to existing methods, but it has relatively high scheduling time. In this paper, we propose a deep learning-based dynamic scheduling with multi-agents supporting scalability in edge computing environments. The proposed method shows low scheduling time than previous artificial intelligence-based scheduling techniques. To show the effectiveness of the proposed method, we compare the performance between previous and proposed methods in a scalable experimental environment. The results show that our method supports real-time IoT applications with low scheduling time, and shows better performance in terms of the number of completed cloud tasks in a scalable experimental environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.115-121
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• 2015

In this paper, we proposed an iterative data-flow optimal scheduling algorithm based on genetic algorithm for high-performance multiprocessor. The basic hardware model can be extended to include detailed features of the multiprocessor architecture. This is illustrated by implementing a hardware model that requires routing the data transfers over a communication network with a limited capacity. The scheduling method consists of three layers. In the top layer a genetic algorithm takes care of the optimization. It generates different permutations of operations, that are passed on to the middle layer. The global scheduling makes the main scheduling decisions based on a permutation of operations. Details of the hardware model are not considered in this layer. This is done in the bottom layer by the black-box scheduling. It completes the scheduling of an operation and ensures that the detailed hardware model is obeyed. Both scheduling method can insert cycles in the schedule to ensure that a valid schedule is always found quickly. In order to test the performance of the scheduling method, the results of benchmark of the five filters show that the scheduling method is able to find good quality schedules in reasonable time.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.61-67
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• 2000

In case of the remote controllable web-camera that was took notice especially in internet real-time broadcasting systems, a great many clients connect the server of web-camera to request the service. So, the scheduling methods are important. Web-camera systems have used to the traditional FIFO(First In First Out) or SDF(Shortest Distance First) scheduling method. But they does not satisfy both the minimization of moving distance on the web-camera and the fairness on the users. In this paper, We propose the 2D scheduling method, As a result, the moving distance of the web-camera decreases compared with FIFO scheduling method. And the starvation state on the user's request does not happen compared with SDF scheduling method. Thus, if the remote controllable web-camera systems use the 2D scheduling method, they are satisfied with the minimization of moving distance on the remote controllable web-camera and the fairness on the users simultaneously. Therefore the user's satisfaction and the performance of the systems are improved.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1053-1068
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• 2003

In this paper, we propose a new scheduling method without timing covert channel of real-time transaction for secure database systems that implement mandatory access control. Our scheduling method use the wait queue based on security level to remove timing covert channel. And it use priority queue that consider transaction type, deadline, and weight. Therefore, the proposed scheduling method prevents timing covert channel because it is kept noninterference between transactions with different security level, and maximizes the sum of the weight of transactions that satisfy its deadline. The simulation results, is a comparison of traditional methods, show that our scheduling method is improved to 30%.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.3
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• pp.153-161
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• 2002

In this paper, we propose a Probabilistic Tabu Search(PTS) method for hydro-thermal scheduling. Hydro scheduling has many constraints and very difficult to solve the optical schedule because it has many local minima. To solve the problem effectively, the proposed method uses two procedures, one is Tabu search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify its search region. To adjust Parameters such as a reducing rate and initial searching region, search strategy is selected according to its probability after restarting procedure. Dynamic decoding method was also used to restrict a search region and to handle water balance constraints. In order to show the usefulness of the proposed method, the PTS is applied on two cases which have independent or dependent hydro plants and compared to those of other method. The simulation results show it is very efficient and useful algorithm to solve the hydro-thermal scheduling problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.241-251
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• 1998

There are two methods of load balancing for detail scheduling : One method is to generate an initial schedule and obtain an improved final schedule by load balancing only during a specific period. The other method is to generate an initial schedule and obtain an improved schedule by load balancing from current date(TIMENOW) to unlimited time with the whole manufacturing processes. This paper proposes an algorithm for detail scheduling which can be a practical solution in job shop production or project job type by applying the former method.