• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.113-119
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• 2009

In this paper, we proposed an efficient TDMA scheduling algorithm for a clustered Wireless Sensor Network. Since some previous algorithms used unnecessary idle period and schedule period in each frame. It became an overhead that might consume unexpected energy and delay data transmission. To solve this problem, a dynamic scheduling algorithm according to the number of member nodes and node traffic load within a cluster was suggested. Our proposed DS-MAC(Dynamic Scheduling MAC) could save energy and reduce transmission delay Then DS-MAC was analyzed mathematically to compare with the previous algorithms.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.237-244
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• 2013

We propose Energy-constrained Multiprocessor Real-Time Scheduling algorithms for (m,k)-firm deadline constrained tasks (EMRTS-MK). Rather than simply saving as much energy as possible, we consider energy as hard constraint under which the system remains functional and delivers an acceptable performance at least during the prescribed mission time. We evaluate EMRTS-MKs in several experiments, which quantitatively show that they achieve the scheduling objectives.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.101-109
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• 2008

This paper considers an integrated decision for scheduling and outsourcing(or, subcontracting) of a finite number of jobs(or, orders) in a time-sensitive make-to-order manufacturing environment. The jobs can be either processed in a parallel in-house facilities or outsourced to subcontractors. We should determine which jobs should be processed in-house and which jobs should be outsourced. And, we should determine the schedule for the jobs to be processed in-house. If a job is determined to be processed in-house, then the scheduling cost(the completion time of the Job) is imposed. Otherwise(if the job should be outsourced), then an additional outsourcing cost is imposed. The objective is to minimize the linear combination of scheduling and outsourcing costs under a budget constraint for the total available outsourcing cost. In the problem analysis, we first characterize some solution properties and then derive dynamic programming and branch-and- bound algorithms. An efficient heuristic is also developed. The performances of the proposed algorithms are evaluated through various numerical experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5243-5263
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• 2017

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11B
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• pp.1631-1639
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• 2010

This paper proposes a scheduling algorithm that can reduce the power consumed for execution of application programs and the communication cost incurred due to dependencies among tasks. The proposed scheduling algorithm can increase energy efficiency of the DVS(Dynamic Voltage Scaling) by estimating laxity usage during scheduling, making up for conventional algorithms that apply the DVS after scheduling. Energy efficiency can be increased by applying the proposed algorithm to complex multimedia applications. Experimental results show that energy consumptions for executing HD MPEG4, MotionJPEG codec, MP3, and Wavelet have been reduced by 11.2% on the average, when compared to conventional algorithms.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.234-240
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• 1999

This paper presents a new approach for large-scale generator maintenance scheduling optimizations. The generator preventive maintenance scheduling problems are typical discrete dynamic n-dimensional vector optimization ones with several inequality constraints. The considered objective function to be minimized a subset of{{{{ { R}^{n } }}}} space is the variance (i.g., second-order momentum) of operating reserve margin to levelize risk or reliability during a year. By its nature of the objective function, the optimal solution can only be obtained by enumerating all combinatorial states of each variable, a task which leads to computational explosion in real-world maintenance scheduling problems. This paper proposes a new priority search mechanism based on each generator's discrete sensitivity value which was analytically developed in this study. Unlike the conventional capacity-based priority search, it can prevent the local optimal trap to some extents since it changes dynamically the search tree in each iteration. The proposed method have been applied to two test systems (i.g., one is a sample system with 10 generators and the other is a real-world lage scale power system with 280 generators), and the results anre compared with those of the conventional capacith-based search method and combinatorial optimization method to show the efficiency and effectiveness of the algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.11-16
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• 2010

This paper compares and studies scheduling methods to reduce jitter in real-time control systems. While previous research has focused on dynamic-priority scheduling schemes, this paper focuses on fixed-priority scheduling which is more widely used. It is pointed out that previously defined jitter measures might not be useful in enhancing the control performance of a real-time task because the measures are relative values. We present a new jitter measure and a new scheduling scheme for fixed-priority tasks. The experimental results through simulation show that the new scheduling scheme reduces jitter and enhances control performance.

• Proceedings of the Korea Association of Information Systems Conference
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• 2003.05a
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• pp.1-20
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• 2003

In this research, we developed a Multi-Agent based Negotiation Support System to be able to increase the competitive power of a company in dynamic environment and correspond to various orders of customers by diffusion of electronic commerce. The system uses the agent technology that is being embossed as new paradigm in dynamic environment and flexible system framework. The multi-agent technology is used to solve these problem through cooperation of agent. The system consists of six sub agents: mediator, manufacturability analysis agent, process planning agent, scheduling agent, selection agent, negotiation-strategy building agent. In this paper, the proposed Multi-Agent based Negotiation Support System takes aim at the automation of transaction process from ordering to manufacturing plan through the automation of negotiation that is the most important in order-taking transaction.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.286-291
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• 2001

This paper describes an optimal scheduling for ice slurry systems for energy cost saving. The optimization technique applied in the study is the dynamic programming method, for which the state variable is the storage in the ice storage tank and the control variable is the state of chiller's on-off switching. Though the costs during charge period is included in optimization by taking the average cost of ice per hour for slurry making, the time horizon for the simulation is limited building cooling period because accurate charge rate from the ice maker into the ice storage tank cannot be estimated during the charge period. In the operating simulation after optimizing procedure, energy consumption and operating cost for the optimal control are calculated and compared with them for a conventional control with one case of cooling load profile.