• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.519-522
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• 1998

The Constructive Battle simulation Model is very important to the recent military training for the substitution of the field training. However, real battlefield systems operate under rea-time conditions, they are inherently distributed, concurrent and dynamic. In order to reflect these properties by the computer-based simulation systems which represent real world processes, we have been developing constructive simulation model for several years. The constructive simulation system is one of the famous real-time system software, nd the one common feature of all real-time systems is defined as the correctness of the system depend not only on the logical result of computation, but also on the time at which the results are produced. Conventionally, scheduling and resource allocation activities which have timing constraints are major problem of real-time computing systems. To overcome these constraints, we elaborated on these issues and developed the simulation system on commercially available hardware and operating system with lock-free resource allocation scheme and rae monotonic scheduling.

• The Journal of Information Technology
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• v.4 no.4
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• pp.65-72
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• 2001

This paper investigates the Performance of MSA l (group partition based reservation scheduling algorithm) and MSA ll (group based reservation scheduling algorithm) for multicast service in single-hop WDM networks. Simulation results show that MSA l produces lower mean packet delay than MSA ll when the channel resource is sufficient. However, when the channel resource is limited, MSA ll produces lower mean packet delay than MSA I when traffic load is heavy.

• IE interfaces
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• v.12 no.4
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• pp.586-594
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• 1999

This paper introduces a production scheduling system for the block assembly shop in a shipbuilding company. We are to make a schedule for the assembly shop and related subassembly production shop. The objectives of the scheduling system are balancing of the workload of the subassembly shops as well as the assembly shop. There are a number of technological and resource constraints including assembly space restriction which is most important and critical resource in the shop. It is very hard and time consuming to consider the two problems, the workload balancing and the spatial allocation problem, simultaneously, and hence, we analyze the two problems independently. The first problem has already been introduced(고시근, 1996), and the overall appearance of the system and the spatial allocation algorithm are presented in this paper.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.201-207
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• 2021

Edge Computing enables image-based inference in close proximity to end users and real-world objects. However, since edge servers have limited computational and accelerator resources, efficient resource management is essential. In this paper, we present HeteroAccel system that performs optimal scheduling in Kubernetes platform based on available node and accelerator information for various inference requests. Our experiments showed 25.3% improvement in overall inference performance over the default scheduling scheme in edge computing environment in which four types of inference services are requested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5917-5935
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• 2018

Adaptive Multi-Rate Codec is one of the codecs which is used for making voice calls. It helps to connect people who are scattered in various geographical areas. It adjusts its bit-rate according to the user's channel conditions. It plays a vital role in providing an improved speech quality of voice connection in Long Term Evolution (LTE). There are some constraints which need to be addressed in providing this service profitably. Quality of Service (QoS) is the dominant mechanism which determines the quality of the speech in communication. On several occasions, number of users are trying to access the same channel simultaneously by standing in a particular region for a longer period of time. It refers to Multi-user channel sharing problem which leads to resource loss very often. The main aim of this paper is to develop a novel RSA - QoS scheduling algorithm for reducing the Resource Loss Ratio. Eventually, it increases the throughput.The simulation result shows that the RSA - QoS increases the number of users for accessing the resources better than the existing algorithms in terms of resource loss and throughput. Ultimately, it enhances the QoS in Mobile Networks.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.171-180
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• 2009

Population learning algorithm (PLA) is a population-based method that was inspired by the similarities to the phenomenon of social education process in which a diminishing number of individuals enter an increasing number of learning stages. The study aims to develop a framework that repeatedly applying the PLA to solve the discrete resource constrained project scheduling problem with two objectives: minimizing project makespan and renewable resource availability, which are two most common concerns of management when a project is being executed. The PLA looping framework will provide a number of near Pareto optimal schedules for the management to make a choice. Different improvement schemes and learning procedures are applied at different stages of the process. The process gradually becomes more and more sophisticated and time consuming as there are less and less individuals to be taught. An experiment with ProGen generated instances was conducted, and the results demonstrated that the looping framework using PLA outperforms those using genetic local search, particle swarm optimization with local search, scatter search, as well as biased sampling multi-pass algorithm, in terms of several performance measures of proximity. However, the diversity using spread metric does not reveal any significant difference between these five looping algorithms.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.4
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• pp.359-371
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• 2001

Project scheduling under resource constraint conditions have contained to many uncertain factors and it is perfonned by human experts. The expert identifies the activities of the project, decides the precedent relationships between these activities, and then construct the schedule using expected activity's duration. At this time, most of the scheduling methods concentrate on one of scheduling factor between activity duration and cost. And the activity duration, which is the most important factor in scheduling, is decided by heuristic of expert. Therefore it may cause uncertainty of activity duration decision and the use of this activity duration may increase the uncertainty of constructed schedule. This paper proposes Fuzzy-MOEH scheduling algorithm, which is the aggregation of the fuzzy number for deciding activity duration and applies the cost function for solving the problems of previous scheduling methods. This paper also analyze the utility and property of Fuzzy-MEOH algorithm through the comparison between Fuzzy-MEOH algorithm and existing MEOH algorithm.

• ETRI Journal
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• v.30 no.1
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• pp.1-12
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• 2008

In this paper, we propose an efficient single-resource task scheduling algorithm for the Communication, Ocean, and Meteorological Satellite. Among general satellite planning functions such as constraint check, priority check, and task scheduling, this paper focuses on the task scheduling algorithm, which resolves conflict among tasks which have an exclusion relation and the same priority. The goal of the proposed task scheduling algorithm is to maximize the number of tasks that can be scheduled. The rationale of the algorithm is that a discarded task can be scheduled instead of a previously selected one depending on the expected benefit acquired by doing so. The evaluation results show that the proposed algorithm enhances the number of tasks that can be scheduled considerably.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.108-117
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• 2015

Interrupt handling is generally separated from process scheduling. This can lead to a scheduling anomaly and priority inversion. The processor can interrupt a higher priority process that is currently executing, in order to handle a network packet reception interruption on behalf of its intended lower priority receiver process. We propose a new network interrupt handling scheme that combines interrupt handling with process scheduling and the priority of the process. The proposed scheme employs techniques to identify the intended receiver process of an incoming packet at an earlier phase. We implement a prototype system of the proposed scheme on Linux 2.6, and our experiment results show that the prototype system supports the predictable real-time behavior of higher priority processes even when excessive traffic is sent to lower priority processes.