• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.763-766
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• 2011

Timely management is an important activity in long running transactions. This can be seen in many Supply Chain scenarios where insufficient time management could lead to expensive compensations. Therefore, effective strategy for timely management in long running transactions is needed. In this paper, we propose our solution to detect and avoid violating deadline based on a comparison strategy of predicted complete time and required deadline. Three approaches are used. Firstly, we build Open Nested Transaction Model (ONTM) where deadline of top-level transactions are managed through a flexible time adjustment of lower level transactions. Secondly, workflow is introduced to WSTransaction framework which supports the algorithm to predict complete time and spot delaying activities. Thirdly, a rule-based coordinator is developed to decide the confirmation or cancelation of participants' ongoing activities. We also discuss a workflow example for implementation.

• Journal of KIISE
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• v.44 no.1
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• pp.107-113
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• 2017

Real-time multicasting is a packet transmission scheme ensuring that multiple destinations receive a packet within the desired time line. In wireless sensor networks, a packet can be delivered to a limited distance under a given deadline, since the end-to-end delay tends to be proportional to the end-to-end physical distance. Existing real-time multicasting protocols select the distance between the source and the furthest destination as the distance limitation and construct a multicasting tree guaranteeing delivery paths to each destination within the distance limitation. However, the protocols might lead to real-time delivery failures and energy efficiency degradation due to the fixed distance limitation. In this study, we proposed a real-time multicasting protocol using time deadline. The proposed protocol obtains the maximum transmittable distance with a given time deadline and subsequently constructs a multicasting tree using the maximum transmittable distance. The form of the multicasting tree varies according to the given time deadline to trade off the energy efficiency against the real-time delivery success ratio. The simulation results showed that the proposed scheme is superior to the existing protocols in terms of energy efficiency and real-time delivery success ratio under various time deadlines.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.2
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• pp.27-34
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• 2013

NAND Flash Memory has been used in several devices by low cost and high capacity, and the demand for mass NAND Flash Memory has increased due to the multimedia extension of mobile devices. The JFFS2, NILFS2, and YAFFS2 file systems are used mainly in NAND Flash Memory. In this paper, the performance of Sequential read/write of the 3 file systems are analyzed for the 4 I/O schedulers : CFQ(Complete Fair Queuing) I/O scheduler, NOOP(No Operation) I/O scheduler, Anticipatory I/O scheduler, and Deadline I/O scheduler. In JFFS2 file system, Anticipatory I/O scheduler has the best performance by 8% decreasing speed in writing time and 1.5% decreasing speed in reading time compared to the other I/O scheduler. In YAFFS2 file system, it results are similar to performance in reading and writing for the 4 I/O schedulers. In NILFS2 file system, NOOP I/O scheduler has 2% faster in writing and Deadline I/O scheduler has 6% faster in reading than other I/O schedulers.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.1
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• pp.9-20
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• 2009

In a real-time system with both hard real-time periodic tasks and soft real-time aperiodic tasks, it is important to guarantee the deadlines of each periodic task as well as obtain fast response time for each aperiodic task. This paper proposes Enhanced Total Bandwidth Server (ETBS) with possibly shorter response time than Total Bandwidth Server (TBS), which is efficient and widely used for servicing aperiodic tasks. For uniprocessor system using Earliest Deadline First (EDF) scheduling algorithm, ETBS assigns an on-line deadline to each aperiodic task considering a surplus slack time which gained for every unit execution time of periodic job. The proposed method can fully utilize the processor while meeting all the deadlines of periodic tasks. We show that the proposed ETBS provides better response time of aperiodic tasks than TBS theoretically, but has the same computational complexity as TBS, O(1). Simulation results show that the response time of aperiodic tasks with ETBS are shorter than one with TBS.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.2
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• pp.68-74
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• 2005

In deadline scheduling, jobs have deadlines by which they are completed. The scheduling algorithm determines which jobs are executed at each time. Then only the completed jobs contribute to the throughput or gain of the algorithm. The jobs have arbitrary weights and the gain of the algorithm is given as the sum of weights of the completed jobs. The goal of the scheduling algorithm is to maximize its gain. In this paper, we consider online non-preemptive scheduling, where jobs arrive online and the scheduling algorithm has no information about jobs arriving ahead. Also the jobs cannot be preempted or rejected while they are executed. For this problem, we obtain lower bounds for any online algorithms and also we propose an optimal online algorithm meeting the lower bounds.

• 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.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.115-121
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• 2010

It always must guarantee preceding process of the transaction with the higher priority in real-time database systems. The pessimistic concurrency control method resolves a conflict through aborting or blocking of a low priority transaction. However, if a high priority transaction is eliminated in a system because of its deadline missing, an unnecessary aborting or blocking of a low priority transaction is occurred. In this paper, the proposed method eliminates a transaction that is about to miss its deadline. And it prevents needless wastes of resources and eliminates unnecessary aborting or blocking of a low priority transaction. It is shown through the performance evaluation that the proposed method outperforms the existing methods in terms of the deadline missing ratio of transactions.

• The KIPS Transactions:PartA
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• v.16A no.1
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• pp.35-42
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• 2009

This paper proposes a new coverage algorithm for intelligent robot. Many algorithms for improving the performance of coverage have been focused on minimizing the total coverage completion time. However, if one does not have enough time to finish the whole coverage, the optimal path could be different. To tackle this problem, we propose a new coverage algorithm, which we call MaxCoverage algorithm, for covering maximal area within the deadline. The MaxCoverage algorithm decides the navigation flow by greedy algorithm for Set Covering Problem. The experimental results show that the MaxCoverage algorithm performs better than other algorithms for random deadlines.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.15 no.1
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• pp.22-28
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• 2008

Purpose: The aim of this study was to analyze the effects of time management on the clinical nurse's organizational commitment and job satisfaction. Methods: Subjects were recruited in two general hospitals in Seoul and Incheon. Data collection was done using a self-report questionnaire. Time management was measured using the questionnaire developed by Han (1992). Organizational commitment and job satisfaction were measured using the questionnaire developed by Yoon (2000), based on Mowday et al. (1979) and Stamps et al. (1978). The data were analyzed using the SAS statistical package program, version 10.0. Specifically, descriptive statistics and stepwise multiple regression were performed. Results: The predictive time management factors for organizational commitment included deadline decision, simplification, and goal-setting. The predictive time management factors for job satisfaction included planning/making the priority order, deadline decision, simplification, asking for help, and responsibility reduction. Conclusion: Time management factors are highly correlated with organizational commitment and job satisfaction in clinical nurses. Deadline decision and simplification are common predictive factors for organizational commitment and job satisfaction. These results can be used to develop more effective time management strategies for increasing organizational effectiveness in clinical nurses.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.70-79
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• 2010

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.