• 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 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 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.

• ETRI Journal
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• v.26 no.5
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• pp.391-396
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• 2004

In this paper, we propose a packet scheduling discipline called packet loss fair scheduling, in which the packet loss of each user from different real-time traffic is fairly distributed according to the quality of service requirements. We consider an orthogonal frequency division multiple access (OFDMA) system. The basic frame structure of the system is for the downlink in a cellular packet network, where the time axis is divided into a finite number of slots within a frame, and the frequency axis is segmented into subchannels that consist of multiple subcarriers. In addition, to compensate for fast and slow channel variation, we employ a link adaptation technique such as adaptive modulation and coding. From the simulation results, our proposed packet scheduling scheme can support QoS differentiations while guaranteeing short-term fairness as well as long-term fairness for various real-time traffic.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.701-706
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• 1994

Holonic manufacturing system is a new approachto the organization and architecture of decentralized, autonomous and cooperative manufacturing system. The new paradigm combines the concepts of hierarchical systems and the integration of autonomous elements in distributed system. Today's scheduling and control techniques are mostly based on a centralized structure. Only little work has been done on scheduling and control of decentralized, autonomous and cooperative manufacturing system. This paper proposes a new approach IPM(Interactive Prediction Method) for scheduling and control of holonic manufacturing system.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2521-2532
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• 1998

This paper proposes Heterogeneous Duplicatio Scheduling(HDS) which alleviates excessive communication overhead between tasks for distributed computing on a teerogeneous distributed environment. HDS is to allocate a copy of a task that causes excesive data communication with a message receiving task to the dame machine wherein the message receiving task is scheduled. The proposed algorithm allows only the duplication of parent tasks so as not to increase the complexity of the algorithm. Simulation on various type of task graphs provides that the scheduling results by using HDS are better than those by using the existing geterogencous cheduling schemes.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.91-100
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• 2016

In this research, emergency vehicle dispatching problems faced with in the wake of massive natural disasters are considered. Here, the emergency vehicle dispatching problems can be regarded as a single machine stochastic scheduling problems, where the processing times are independently and identically distributed random variables, are considered. The objective of minimizing the expected number of tardy jobs, with distinct job due dates that are independently and arbitrarily distributed random variables, is dealt with. For these problems, optimal static-list policies can be found by solving corresponding assignment problems. However, for the special cases where due dates are exponentially distributed random variables, using a proposed dynamic programming approach is found to be relatively faster than solving the corresponding assignment problems. This so-called Pivot Dynamic Programming approach exploits necessary optimality conditions derived for ordering the jobs partially.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.549-557
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• 2000

Distributed Memory Machine(DMM) is necessary for the effective computation of the data which is complicated and very large. Task scheduling is a method that reduces the communication time among tasks to reduce the total execution time of application program and is very important for the improvement of DMM. Task Duplicated based Scheduling(TDS) method improves execution time by reducing communication time of tasks. It uses clustering method which schedules tasks of the large communication time on the same processor. But there is a problem that cannot optimize communication time between task sending data and task receiving data. Hence, this paper proposes a new method which solves the above problem in TDS. Modified Task Duplicated based Scheduling(MTDS) method which can approximately optimize the communication time between task sending data and task receiving data by checking the optimal condition, resulted in the minimization of task execution time by reducing the communication time among tasks. Also system modeling shows that task execution time of MTDS is about 70% faster than that of TDS in the best case and the same as the result of TDS in the worst case. It proves that MTDS method is better than TDS method.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1201-1210
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• 2000

In order to tolerate faults which may occur during the execution of distributed tasks in high-performance parallel computer systems, tasks are duplicated on different processors. In this paper, by utilizing the task duplication based scheduling algorithm, a new task scheduling algorithm which duplicates each task on more than two different processors with the minimum schedule length is presented, and the number of processors required for the duplication is analyzed with the ratio of communication cost to computation time and the workload of the system. A simulation with various task graphs reveals that the number of processors required for the full-duplex fault-tolerant task scheduling with the obtainable minimum schedule length increases about 30% to 75% when compared with that of the task duplication based scheduling algorithm.