• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3566-3582
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• 2019

In intelligent warehouse picking system, the allocation of tasks has an important influence on the efficiency of the whole system because of the large number of robots and orders. The paper proposes a method to solve the task allocation problem that multi-robot task allocation problem is transformed into transportation problem to find a collision-free task allocation scheme and then improve the capability of task processing. The task time window and the power consumption of multi-robot (driving distance) are regarded as the utility function and the maximized utility function is the objective function. Then an integer programming formulation is constructed considering the number of task assignment on an agent according to their battery consumption restriction. The problem of task allocation is solved by table working method. Finally, simulation modeling of the methods based on table working method is carried out. Results show that the method has good performance and can improve the efficiency of the task execution.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.415-420
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• 2012

It is important to understand the amount of time required to execute an emergency procedural task in a high-stress situation for managing human performance under emergencies in a nuclear power plant. However, the time to execute an emergency procedural task is highly dependent upon expert judgment due to the lack of actual data. This paper proposes an analytical method to estimate the operator's performance time (OPT) of a procedural task, which is based on a measure of the task complexity (TACOM). The proposed method for estimating an OPT is an equation that uses the TACOM as a variable, and the OPT of a procedural task can be calculated if its relevant TACOM score is available. The validity of the proposed equation is demonstrated by comparing the estimated OPTs with the observed OPTs for emergency procedural tasks in a steam generator tube rupture scenario.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2659-2669
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• 1999

This paper a heuristic, clustering based task allocation scheme applicable to non-directed task graph on a distributed system. This scheme firstly builds a task-machine graph, and then applies a clustering process where in a pair of tasks that are connected to the highest cost edge is merged into a big one or a task is allocated to a machine. During the process, the proposed scheme figure out a machine onto which the task allocation may cause deduction of large communication overhead that has incurred between the task and tasks that are already allocated to the machine while the computation costs is slightly increased in the machine. Simulation for the various task graphs shows that the scheduling using the proposed scheme result far better than ones by using the traditional schemes. A comparison with optimal task scheduling also promises that our scheme derives optimal results more occasionally than the traditional schemes do.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.149.3-149
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• 2001

Task allocation is a key problem in multiagent systems. The importance of automated negotiation protocols for solving the task allocation problem is increasing as a consequence of increased multi-agent applications. In this paper, we introduce the multiagent Traveling Salesman Problem(TSP) as an example of task reallocation problem, and suggest Vickery auction as an inter-agent coordination mechanism for solving this problem. In order to apply this market-based coordination mechanism into multiagent TSPs, we define the profit of each agent, the ultimate goal of negotiation, cities to be traded out through auctions, the bidding strategy, and the order of auctions. The primary advantage of such approach is that it can find an optimal task allocation ...

• The Journal of Information Systems
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• v.16 no.1
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• pp.179-200
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• 2007

In this research, we study how task and KMS fit influences on KMS performance in large corporations during its practical use. Based on the task-technology fit theory and information system success model, we developed a research model by considering the characteristics of KMS for supporting tasks. We try to verify how individual traits, task traits, and KMS Units affect task-KMS fit and how task KMS fit influences on KMS performance. We surveyed 212 employees who were using KMS and working for the large-sized manufacturing firms. We analyzed the collected data from LISREL 8.54 for Windows, and found the following significant results. First user satisfaction is increased when KMS provides knowledge to help to perform task rather than KMS' functionality. Second, user satisfaction is increased when KMS is suitable for performing task Hence, we verified task-KMS fit is an antecedent of user satisfaction. Third, task-KMS fit and user satisfaction have significant impacts on KMS performance. And user satisfaction affected more heavily on KMS performance than task-KMS fit did. As a result, we realized an individual performance can be improved when task KMS fit is high and, consequently, user satisfaction is increased. Forth while the usefulness of task-KMS fit is demonstrated, causal factors such as individual traits, task traits, and KMS traits significantly affect task-KMS fit. Formalization and knowledge trait we significant in enhancing user satisfaction, but KMS self-efficacy, autonomy, md system trait are not. These results indicate that task-KMS fit variable is useful as a measure of KMS performance as well as that of user satisfaction. Based on these results, we conclude that when KMS supports task activity, performance can be significantly improved by coordinating the task with KMS.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.243-246
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• 1996

Modular robot manipulator is a robotic system assembled from discrete joints and links into one of many possible manipulator configurations. This paper describes the design method of newly developed modular robot manipulator and the methodology of a task based reconfiguration of it. New locking mechanism is proposed and it provides quick coupling and decoupling. A parallel connection method is devised and it makes modular robot manipulator working well and the number of components on each module reduced. To automatically determine a sufficient or optimal arrangement of the modules for a given task, we also devise an algorithm that automatically generates forward and inverse manipulator kinematics, and we propose an algorithm which maps task specifications to the optimized manipulator configurations. Efficient genetic algorithms are generated and used to search for a optimal manipulator from task specifications. A few of design examples are shown.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.51-57
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• 2021

In this paper, we propose a task distribution scheme in fog computing environment considering opportunistic fog computing nodes. As latency is one of the important performance metric for IoT(Internet of Things) applications, there have been lots of researches on the fog computing system. However, since the load can be concentrated to the specific fog computing nodes due to the spatial and temporal IoT characteristics, the load distribution should be considered to prevent the performance degradation. Therefore, this paper proposes a task distribution scheme which considers the static as well as opportunistic fog computing nodes according to their mobility feature. Especially, based on the task requirements, the proposed scheme supports the delay sensitive task processing at the static fog node and delay in-sensitive tasks by means of the opportunistic fog nodes for the task distribution. Based on the performance evaluation, the proposed scheme shows low service response time compared to the conventional schemes.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• English Language & Literature Teaching
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• v.18 no.2
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• pp.45-66
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• 2012

The purpose of this study was to investigate the impact of two different SNS-based tasks on university students' English writing performance. To address our primary research question, Me2day, microblogging and Social Networking Service, was employed. 43 university students were divided into two experimental groups depending on the task types: a comparison task group and a sharing personal experiences task group. The main findings of the study were as follows: first, two different types of SNS-based tasks, 'spot the differences' and 'writing diaries', had a positive effect on learners' writing performance. The reason for this was that the succinct messages limited to 150 characters made it easier for the students to try writing in English without burden; and they may benefit from their peers by seeing their posts and interacting with each other. Yet there were no significant differences between the two groups when it came to the degree of improvement. Second, two different types of SNS-based tasks differently fostered certain aspects of the writing performance; 'contents knowledge' was supported by the 'writing diaries' task and range was supported by the 'spot the differences' task. Third, learners in the two experimental groups mostly had positive impressions regarding usage of Me2day as a new learning tool.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3C
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• pp.219-233
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• 2008

Optimal scheduling of parallel tasks with some precedence relationship, onto a parallel machine is known to be NP-complete. The complexity of the problem increases when task scheduling is to be done in a heterogeneous environment, where the processors in the network may not be identical and take different amounts of time to execute the same task. This paper introduces a Duplication based Task Scheduling with Communication Cost in Heterogeneous Systems (DTSC), which provides optimal results for applications represented by Directed Acyclic Graphs (DAGs), provided a simple set of conditions on task computation and network communication time could be satisfied. Results from an extensive simulation show significant performance improvement from the proposed techniques over the Task duplication-based scheduling Algorithm for Network of Heterogeneous systems(TANH) and General Dynamic Level(GDL) scheduling algorithm.