• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.891-898
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• 2010

In real software development fields, software is unified by several modules that are developed before the software testing period. For the evaluation of software task processing performance, this paper considers the software imperfect debugging model that is proposed by Lee and Park (2003) and presents the measures of a unified software, such as the completion probability of a task which is completed in a time interval and the expected number of the completed tasks. In addition, we suggest a software release policy that satisfies the required level of the expected perfect debugging, completion probability, and availability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5652-5659
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• 2014

The purpose of this study was to introduce a software task processing evaluation model that considers the following situations: i) a software system is integratedly composed of several number of modules, ii) each modules has its corresponding module task, iii) all module tasks are tested simultaneously, and iv) the processing times of the module tasks are mutually dependent. The software task completion probability with the module dependency was derived using the joint distribution function of Farlie [11]. The results showed that the task completion probability of software increases with increasing module dependency parameter.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.61-69
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• 2022

A multi-agent system is a system that aims at achieving the best-coordinated decision based on each agent's local decision. In this paper, we consider a multi agent-multi task assignment problem. Each agent is assigned to only one task and there is a completion probability for performing. The objective is to determine an assignment that maximizes the sum of the completion probabilities for all tasks. The problem, expressed as a non-linear objective function and combinatorial optimization, is NP-hard. It is necessary to design an effective and efficient solution methodology. This paper presents an approximation algorithm using submodularity, which means a marginal gain diminishing, and demonstrates the scalability and robustness of the algorithm in theoretical and experimental ways.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.27-34
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• 2023

The optimal assignment problem between agents and tasks is known as one of the representative problems of combinatorial optimization and an NP-hard problem. This paper covers multi agent-multi task assignment problems with uncertain completion probability. The completion probabilities are generally uncertain due to endogenous (agent or task) or exogenous factors in the system. Assignment decisions without considering uncertainty can be ineffective in a real situation that has volatility. To consider uncertain completion probability mathematically, a mathematical formulation with stochastic programming is illustrated. We also present an algorithm by using the sample average approximation method to solve the problem efficiently. The algorithm can obtain an assignment decision and the upper and lower bounds of the assignment problem. Through numerical experiments, we present the optimality gap and the variance of the gap to confirm the performances of the results. This shows the excellence and robustness of the assignment decisions obtained by the algorithm in the problem with uncertainty.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.376-380
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• 2008

This paper deals with a performance analysis of real-time control systems, which engages DMR(dual modular redundancy) to detect transient errors and checkpointing technique to tolerate transient errors. Transient errors are caused by transient faults and the most significant type of errors in reliable computer systems. Transient faults are assumed to occur according to a Poisson process and to be detected by a dual modular redundant structure. In addition, an equidistant checkpointing strategy is considered. The probability of the successful task completion in a real-time control system where periodic checkpointing operations are performed during the execution of a real-time control task is derived. Numerical examples show how checkpoiniting scheme influences the probability of task completion. In addition, the result of the analysis is compared with the simulation result.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.148-154
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• 2012

For a successful checkpointing strategy, we should place checkpoints so as to optimize fault-tolerance capability of real-time systems. This paper presents a novel scheme of checkpoint placement for real-time systems with periodic multi-tasks. Under the influence of transient faults, multi-tasks are scheduled by the Rate Monotonic (RM) algorithm. The optimal checkpoint intervals are derived to maximize the probability of task completion. In particular, this paper is concerned about the general case that the deadline of a task is longer than the period. Compared with the special condition that the deadline is equal to or less than the period, this general case causes a more complicate test procedure for schedulability of the RM algorithm with respect to a given set of checkpoint re-execution vectors. The probability of task completion is also derived in a more complex form. A case study is given to show the applicability of the proposed scheme.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.997-1006
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• 2008

This paper proposes a new model by combining an infinite-server queueing model for multi-task processing software system with a perfect debugging model based on Markov process with two types of faults suggested by Lee et al. (2001). We apply this model for module and integration testing in the testing process. Also, we compute several measure, such as the expected number of tasks whose processes can be completed and the task completion probability are investigated under the proposed model.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.120-127
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• 2011

Checkpointing is one of common methods of realizing fault-tolerance for real-time systems. This paper presents a scheme to determine checkpoint intervals using probabilistic optimization. The considered real-time systems comprises multiple tasks in which transient faults can happen with a Poisson distribution. Also, multi-tasks are scheduled by the non-preemptive Rate Monotonic (RM) algorithm. In this paper, we present an optimization problem where the probability of task completion is described by checkpoint numbers. The solution to this problem is the optimal set of checkpoint numbers and intervals that maximize the probability. The probability computation includes schedulability test for the non-preemptive RM algorithm with respect to given numbers of checkpoint re-execution. A case study is given to show the applicability of the proposed scheme.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.196-197
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• 2014

Low carbon construction is an important operation management goal such as cost, time, and quality in construction community. This paper introduces a system which measures the variability of carbon dioxide amounts. First, this system allows creating construction operation models of which the level of detail is breakdown into the work task level. Second, the system implements sensitivity analysis along with a ranges of resources that are allocated in an operation model. It facilitates to find the optimal resource combination using the operation performances such as the amount of emissions, operation completion time, and cost. Lastly, it identifies the best fit probability distribution functions of performance criteria given a certain resource combination. It allows project manager to query the percentages to complete the operation within a limitation specified by the system users.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.12
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• pp.1147-1152
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• 2007

This paper deals with a scheme for fault-tolerance improvement of real-time embedded systems, which engages an equidistant checkpointing technique to tolerate transient errors. Transient errors are caused by transient faults which are the most significant type of fault in reliable computer systems. Transient faults are assumed to occur according to a Poisson process and to be detected in a non-concurrent manner (e.g., checked periodically). The probability of the successful real-time task completion in the presence of transient errors is derived with the consideration of the possible effects of the transient errors. Based on this, a condition under which inserting checkpoints improves the fault-tolerance of the system is introduced and an optimal equidistant checkpointing strategy that achieves the highest fault tolerance is presented.