• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.29-33
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes the service prediction-based job scheduling model and present its algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts a processing time of each processing component and distributes a job to processing component with minimum processing time. This paper implements the job scheduling model on the DEVSJAVA modeling and simulation environment and simulates with a case study to evaluate its efficiency and reliability Empirical results, which are compared to the conventional scheduling policies such as the random scheduling and the round-robin scheduling, show the usefulness of service prediction-based job scheduling.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.91-100
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• 2005

Grid computing is widely applicable to various fields of industry including process control and manufacturing, military command and control, transportation management, and so on. In a viewpoint of application area, grid computing can be classified to three aspects that are computational grid, data grid and access grid. This paper focuses on computational grid which handles complex and large-scale computing problems. Computational grid is characterized by system dynamics which handles a variety of processors and jobs on continuous time. To solve problems of system complexity and reliability due to complex system dynamics, computational grid needs scheduling policies that allocate various jobs to proper processors and decide processing orders of allocated jobs. This paper proposes a service prediction-based job scheduling model and present its scheduling algorithm that is applicable for computational grid. The service prediction-based job scheduling model can minimize overall system execution time since the model predicts the next processing time of each processing component and distributes a job to a processing component with minimum processing time. This paper implements the job scheduling model on the DEVS modeling and simulation environment and evaluates its efficiency and reliability. Empirical results, which are compared to conventional scheduling policies, show the usefulness of service prediction-based job scheduling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.83-104
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• 2011

Mobile grid is a combination of grid computing and mobile computing to build grid systems in a wireless mobile environment. The development of network technology is assisting in realizing mobile grid. Mobile grid based on established grid infrastructures needs effective resource management and reliable job scheduling because mobile grid utilizes not only static grid resources but also dynamic grid resources with mobility. However, mobile devices are considered as unavailable resources in traditional grids. Mobile resources should be integrated into existing grid sites. Therefore, this paper presents a mobile grid middleware interconnecting existing grid infrastructures with mobile resources and a mobile service agent installed on the mobile resources. This paper also proposes a mobile resource reliability-based job scheduling model in order to overcome the unreliability of wireless mobile devices and guarantee stable and reliable job processing. In the proposed job scheduling model, the mobile service agent calculates the mobile resource reliability of each resource by using diverse reliability metrics and predicts it. The mobile grid middleware allocated jobs to mobile resources by predicted mobile resource reliability. We implemented a simulation model that simplifies various functions of the proposed job scheduling model by using the DEVS (Discrete Event System Specification) which is the formalism for modeling and analyzing a general system. We also conducted diverse experiments for performance evaluation. Experimental results demonstrate that the proposed model can assist in improving the performance of mobile grid in comparison with existing job scheduling models.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.95-101
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• 2004

The scheduling problem that maps independent tasks to heterogeneous resources in distributed computing systems is known as NP-complete［1］. GRID［2］ is an example of distributed systems that consisted of heterogeneous resources. Many algorithms to solve this problem have been presented［1,3,4,5］. The scheduling algorithm can be classified into static scheduling algorithms and dynmic scheduling algorithms. A dynamic scheduling algorithm can be used when we can not predict the priority of tasks. Moreover, a dynamic scheduling algorithm can be divided into on-line mode algorithm and batch mode algorithm according to the scheduling time［1,6］. In this paper, we propose a new on-line mode scheduling algorithm. By extensive simulation, we can see that our scheduling algorithm outperforms previous scheduling algorithms.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.381-386
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• 2006

In this paper, we designed and implemented a web-based grid scheduling platform(WGridSP), which can model a system and simulate scheduling scheme in grid computing. WGridSP used GridSim, a grid scheduling toolkit in java-environment, as a tool for simulation and is able to Perform resource modeling, task modeling, algorithm compiling, simulation, and Performance evaluation rapidly in web environment. WGridSP can be applied as a foundation for grid research and can be used to analyze the efficiency of scheduling algorithm.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.49-56
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• 2007

This paper deals with grid job allocation and grid resource scheduling to provide a stable and quicker job processing service to grid users. In this paper, we proposed a fuzzy logic-based grid job scheduling model for an effective job scheduling in computational grid environment. The fuzzy logic-based grid job scheduling model measures resource efficiency of all grid resources by a fuzzy logic system based on diverse input parameters like CPU speed and network latency and divides resources into several groups by resource efficiency. And, the model allocates jobs to resources of a group with the highest resource efficiency. For performance evaluation, we implemented the fuzzy logic-based grid job scheduling model on the DEVS modeling and simulation environment and measured reduction rates of turnaround time, job loss, and communication messages in comparison with existing job scheduling models such as the random scheduling model and the MCT(Minimum Completion time) model. Experiment results that the proposed model is useful to improve the QoS of the grid job processing service.

• The Journal of Korean Association of Computer Education
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• v.10 no.3
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• pp.49-56
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• 2007

Grid provides a platform for the efficient execution of large-scale computing in science and engineering. In this environment, resource management and task scheduling are complex undertaking. We designed and implemented a web-based scheduling toolkit(GridTool), which can model a system and simulate scheduling scheme in Grid computing. The GridTool used GridSim, a toolkit in java-environment, as a tool for simulation. The GridTool is able to perform resource modeling, task modeling, algorithm compiling, simulation, and performance evaluation efficiently in web environment. The GridTool can be applied as a platform for Grid research and can be used to analyze the efficiency of scheduling algorithm.

• Journal of Computing Science and Engineering
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• v.7 no.1
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• pp.44-52
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• 2013

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.129-136
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• 2006

Grid computing has been appeared for solving large-scaled data which are not solved by a single computer. Grid computing is a new generation platform which connects geographically distributed heterogeneous resources. However, gathering heterogeneous distributed resources produces many difficult problems. Especially. to assure resource reliability is one of the most critical problems. So, we propose a grid resource scheduling model using grid resource reliability measurement. We evaluate resource reliability based on resource status data and apply it to the grid scheduling model in DEVSJAVA modeling and simulation. This paper evaluates parameters such as resource utilization, job loss and average turn-around time and estimates experiment results of our model in comparison with those of existing scheduling models such as a random scheduling model and a round-robin scheduling model. These experiment results showed that the resource reliability measurement scheduling model provides efficient resource allocation and stable Job processing in comparison with a random scheduling model and a round-robin scheduling model.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.639-645
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• 2005

GRID environments have been developed in distributed heterogeneous computing infrastructure for advanced science and engineering Therefore efficient scheduling algorithms for allocating user job to resources in the GRID environment are required. Many scheduling algorithms have been proposed, but these algorithms are not suitable for the GRID environment. That is the previous scheduling algorithm does not consider network bandwidth between multiple resources. In this paper, we propose a new scheduling algorithm for Global GRID environment and show that our algorithm has better performance than other scheduling algorithms through extensive simulation.