• Journal of the military operations research society of Korea
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• v.25 no.1
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• pp.199-214
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• 1999

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 real-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. Conventionally, scheduling and resource allocation activities which have timing 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 rate monotonic scheduling.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.777-786
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• 2007

This paper presents a modified simulated annealing algorithm to optimize linear scheduling projects with multiple resource constraints and its effectiveness is verified with a proposed problem. A two-stage solution-finding procedure is used to model the problem. Then the simulated annealing and the modified simulated annealing are compared in the same condition. The comparison results and the reasons of improvement by the modified simulated annealing are presented at the end.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.802-807
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• 2005

For linear projects, it has long been known that resource utilization is important in improving work efficiency. However, most existing scheduling techniques cannot satisfy the need for solving such issues. This paper presents an optimization model for solving linear scheduling problems involving resource assignment tasks. The proposed model adopts constraint programming (CP) as the searching algorithm for model formulation, and the proposed model is designed to optimize project total cost. Additionally, the concept of outsourcing resources is introduced here to improve project performance.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.1
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• pp.41-45
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• 1984

A resource constrained scheduling problem that involves trade-off between resources and time is considered. Models are considered. Models are presented as zero-one integer program and objectives of models include minimum project completion time and minimum total project cost.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2406-2412
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• 2015

Multi-user multi-input multi-output (MU-MIMO) system has attracted the 4^th generation wireless network as one of core technique for performance enrichment. In this system rate control is a challenging problem and another problem is optimization. Proper scheduling can resolve these problems by deciding which set of user and at which rate the users send their data. This paper proposes a new multi-parameter based scheduling (MPS) for downlink multi-user multiple-input multiple-output (MU-MIMO) system under space-time block coding (STBC) transmissions. Goal of this MPS scheme is to offer improved link level performance in terms of a low average bit error rate (BER), high packet delivery ratio (PDR) with improved resource utilization and service fairness among the user. This scheme allows the set of users to send data based on their channel quality and their demand rates. Simulation compares the MPS performance with other scheduling scheme such as fair scheduling (FS), normalized priority scheduling (NPS) and threshold based fair scheduling (TFS). The results obtained prove that MPS has significant improvement in average BER performance with improved resource utilization and fairness as compared to the other scheduling scheme.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.29-38
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• 2009

In the computing environment with heterogeneous resources, a job scheduling model is necessary for effective resource utilization and high-speed data processing. And, the job scheduling model has to cope with a dynamic change in the condition of resources. There have been lots of researches on resource estimation methods and heuristic algorithms about how to distribute and allocate jobs to heterogeneous resources. But, existing researches have a weakness for system compatibility and scalability because they do not support the standard language. Also, they are impossible to process jobs effectively and deal with a variety of computing situations in which the condition of resources is dynamically changed in real-time. In order to solve the problems of existing researches, this paper proposes a semantic computing-based dynamic job scheduling model that defines various knowledge-based rules for job scheduling methods adaptable to changes in resource condition and allocate a job to the best suited resource through inference. This paper also constructs a resource ontology to manage information about heterogeneous resources without difficulty as using the OWL, the standard ontology language established by W3C. Experimental results shows that the proposed scheduling model outperforms existing scheduling models, in terms of throughput, job loss, and turn around time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1302-1320
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• 2015

In cloud, everything can be provided as a service wherein a large number of users submit their jobs and wait for their services. hus, scheduling plays major role for providing the resources efficiently to the submitted jobs. The brainwave of the proposed ork is to improve user satisfaction, to balance the load efficiently and to bolster the resource utilization. Hence, this paper roposes an Adaptive Multilevel Scheduling System (AMSS) which will process the jobs in a multileveled fashion. The first level ontains Preprocessing Jobs with Multi-Criteria (PJMC) which will preprocess the jobs to elevate the user satisfaction and to itigate the jobs violation. In the second level, a Deadline Based Dynamic Priority Scheduler (DBDPS) is proposed which will ynamically prioritize the jobs for evading starvation. At the third level, Contest Mapping Jobs with Virtual Machine (CMJVM) is roposed that will map the job to suitable Virtual Machine (VM). In the last level, VM Scheduler is introduced in the two-tier VM rchitecture that will efficiently schedule the jobs and increase the resource utilization. These contributions will mitigate job iolations, avoid starvation, increase throughput and maximize resource utilization. Experimental results show that the performance f AMSS is better than other algorithms.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.1-9
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• 2007

We propose a novel framework for distributed resource management. The framework has the following novel features. First, the resource management system is distributed using resource content information that is characterized by system properties. We argue that a distributed system based on resource content is sufficient to satisfy specific scheduling requests for Quality of Service(QoS) considering workload balance across a grid. Second, the distributed system constructs a hierarchical peer-to-peer network. This peered network provides an efficient message routing mechanism. The simulation results demonstrate that the proposed framework is proficient to satisfy QoS in distributed environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5264-5281
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• 2017

Multihop relay-based cellular networks are attracting much interest because of their throughput enhancement, coverage extension, and low infrastructure cost. In these networks, relay stations (RSs) between a base station (BS) and mobile stations (MSs) drastically increase the overall spectral efficiency, with improved channel quality for MSs located at the cell edge or in shadow areas, and enhanced throughput of MSs in hot spots. These relay-based networks require an advanced radio resource management scheme because the optimal amount of radio resource for a BS-to-RS link should be allocated according to the MS channel quality and distribution, considering the interference among RSs and neighbor BSs. In this paper, we propose optimal resource planning algorithms that maximize the overall utility of relay-based networks under a proportional fair scheduling policy. In the first phase, we determine an optimal scheduling policy for distributing BS-to-RS link resources to RSs. In the second phase, we determine the optimal amount of the BS-to-RS link resources using the results of the first phase. The proposed algorithms efficiently calculate the optimal amount of resource without exhaustive searches, and their accuracy is verified by comparison with simulation results, in which the algorithms show a perfect match with simulations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.49-54
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• 2022

With the recent widespread adoption of general-purpose GPUs (GPGPUs) in cloud systems, maximizing the resource utilization through multitasking in GPGPU has become an important issue. In this article, we show that resource allocation based on the workload classification of computing-bound and memory-bound is not sufficient with respect to resource utilization, and present a new thread block scheduling policy for GPGPU that makes use of fine-grained resource utilizations of each workload. Unlike previous approaches, the proposed policy reduces scheduling overhead by separating profiling and scheduling, and maximizes resource utilizations by co-locating workloads with different bottleneck resources. Through simulations under various virtual machine scenarios, we show that the proposed policy improves the GPGPU throughput by 130.6% on average and up to 161.4%.