• 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.

• Journal of Computing Science and Engineering
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• v.10 no.1
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• pp.9-20
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• 2016

Several task clustering heuristics are proposed for allocating tasks in heterogeneous systems to achieve a good response time in data intensive jobs. However, one of the challenging problems is the process in task scheduling after task allocation by task clustering. We propose a task scheduling method after task clustering, leveraging worst schedule length (WSL) as an upper bound of the schedule length. In our proposed method, a task in a WSL sequence is scheduled preferentially to make the WSL smaller. Experimental results by simulation show that the response time is improved in several task clustering heuristics. In particular, our proposed scheduling method with the task clustering outperforms conventional list-based task scheduling methods.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.193-214
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• 2014

Load balancing is the major benefit of any distributed system. To facilitate this advantage, task duplication and migration methodologies are employed. As this paper deals with dependent tasks (DAG), we used duplication. Task duplication reduces the overall schedule length of DAG along-with load balancing. This paper proposes a new task duplication algorithm at the time of tasks assignment on various processors. With the intention of conducting proposed algorithm performance computation; simulation has been done on the Netbeans IDE. The mesh topology of a distributed system is simulated at this juncture. For task duplication, overall schedule length of DAG is the main parameter that decides the performance of a proposed duplication algorithm. After obtaining the results we compared our performance with arbitrary task assignment, CAWF and HEFT-TD algorithms. Additionally, we also compared the complexity of the proposed algorithm with the Duplication Based Bottom Up scheduling (DBUS) and Heterogeneous Earliest Finish Time with Task Duplication (HEFT-TD).

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.64-71
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• 2004

A daily report is one of the critical documents in construction projects, since it helps them keep track of various as-built information. Despite the important role in progress management, the daily reporting process is time-consuming, and the representation of task information on daily reports are not effective enough to accumulate daily as-built information for further use in project management. Task information is composed of a specific work type and a location where the task is performed, which means that the same type of work is repeated over the locations. However, in many cases the task locations are described differently depending on a reporter's preference or experience. Without representing task location information effectively, it is difficult to accumulate and to reuse as-built information. The objective of this research is to build a framework for generating task information which can be efficiently accumulated and reused for progress management. To do so, this research built a task information model with focusing on the representation of task location associated with a work type, and developed an information system that supports automated and interactive generation of task information.

• Asia pacific journal of information systems
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• v.10 no.3
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• pp.181-197
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• 2000

The purpose of this study is to confirm whether the fit between the task and the information characteristics makes any effects on the user satisfaction. The task is defined as two sub-constructs representing the degree of exception and analyzability. The information characteristics is divided into the degree of aggregation, scope and timeliness of information. User satisfaction was used as a surrogate measure of the performance of information systems. The computer self-efficacy was used to control any confounding effects. Field research method using questionnaires was employed to empirically investigate the relationship among the variables. Findings of the study are summarized as follows: the fit between the task and the aggregation of information and between the task and the scope of information turned out to have significant effects on information system performance. The implication of such results is that under highly exceptional or less analyzable task environment, less-aggregated or broad information is more appropriate.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.115-140
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• 2014

In a dynamic business environment, the enterprise mobility solution for a mobile office (EMS) has been adopted to increase the competitive edge of organizations. By using an EMS, performance is expected to be enhanced. However, the related literature has paid little interest to the impact of system quality in an EMS on the information quality produced by the system. On the basis of socio-technical theory, we posited that the system quality in an EMS influences information quality. In addition, we investigated the relationships between the above two qualities, use and job performance by considering task mobility and task inter-dependence as control variables. Survey respondents were from many industries using EMSs. The result of structural equation modeling shows that system quality positively affects information quality, and other relationships in the model are proven statistically significant. We also found that system quality has stronger impacts on use and job performance than information quality does in EMS. However, system quality does not affect use in case both task mobility and task inter-dependence exist. The theoretical and practical implications of the result are discussed in the paper.

• Journal of Information Technology Applications and Management
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• v.21 no.2
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• pp.99-126
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• 2014

Tourism industry increasingly rely on information technology (IT) to improve the task performance. Many studies suggested that the evidence of IT showed not only task performance improvement but also organizational performance. Drawing from the resource-based view, technology and task fitness, and marketing orientation theories, this study proposes that IT use influences directly the task performance and proved the effectiveness of IT in the organizations of tourism industry. Further, the innovativeness, resources, and marketing orientation are identified as main determinants of IT use. The use of IT can serve as a catalyst in improving task performance for organizations in tourism industry. Based on data collected from surveying people who work in the tourism industry, the present study shed light on these issues. The findings provide a new perspective of IT effectiveness in the tourism industry. Then, we discussed the theoretical and practical implications.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Asia pacific journal of information systems
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• v.11 no.2
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• pp.141-158
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• 2001

This paper examines the effects of environmental uncertainty, structural decentralization, formalization, complexity and task interdependence on the information sharing through information system. 197 firms in Korea are surveyed and analyzed to investigate the relationship between the contextual variables and the information sharing. The result of multiple regression analysis shows that task interdependence, structural decentralization, complexity are significant factors to influence on the Information Sharing. Also, additional analysis shows that task interdependence, structural decentralization are major factors in service industry, and task interdependence, structural complexity are in manufacturing industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3523-3543
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• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.