• Journal of KIISE:Computer Systems and Theory
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• v.29 no.8
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• pp.445-455
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• 2002

In this paper, we present a new task scheduling scheme ior the efficient execution of the tasks of compound nodes of hierarchical task graph(HTG) on shared memory system. The proposed scheme for exploitation functional parallelism is autoscheduling that performs the role of scheduling by processor itself without any dedicated global scheduler. To adapt the proposed scheduling scheme for various platforms, Including a uni-processor systems, Java threads were used for implementation, and the performance is analyzed in comparison with a conventional bit vector method. The experimental results showed that the proposed method was found to be more efficient in its execution time and exhibited good load-balancing when using the experimental parameter values. Furthermore, the memory size could be reduced when using the proposed algorithm compared with a conventional scheme.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.347-352
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• 2004

This thesis deals with a task scheduling on a message-passing system. Scheduling and allocation are very important issues since the inappropriate scheduling of tasks cannot exploit the true potential of the system and it can offset the grain from parallelization. It is difficult to apply previous schemes to message-passing system, because previous schemes assume the shared memory system. This thesis proposes an modified priority function and processor selection technique that consider the problems caused by the difference between previous models and message-passing environments. The priority function includes the cumulative communication cost which causes task execution to be delayed. The processor selection technique avoids the situation that a child task is assigned to the same Processor allocated to its parent task that has other unscheduled child tasks. We showed by some simulations that our modified features of task scheduling algorithm can make the better scheduling results than the previous algorithms.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.367-372
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• 2013

Cloud computing technology has been developing at an increasing expansion rate. Today most of firms are using this technology, making improving the quality of service one of the most important issues. To achieve this, the system must operate efficiently with less idle time and without deteriorating the customer satisfaction. This paper focuses on enhancing the efficiency of a conventional Genetic Algorithm (GA) for task scheduling in cloud computing using Fuzzy Logic (FL). This study collected a group of task schedules and assessed the quality of each task schedule with the user expectation. The work iterates the best scheduling order genetic operations to make the optimal task schedule. General GA takes considerable time to find the correct scheduling order when all the fitness function parameters are the same. GA is an intuitive approach for solving problems because it covers all possible aspects of the problem. When this approach is combined with fuzzy logic (FL), it behaves like a human brain as a problem solver from an existing database (Memory). The present scheme compares GA with and without FL. Using FL, the proposed system at a 100, 400 and 1000 sample size*5 gave 70%, 57% and 47% better improvement in the task time compared to GA.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.71-81
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• 2010

In grid system, Task scheduling based on list scheduling models has showed low complexity and high efficiency in fully connected processor set environment. However, earlier schemes did not consider sufficiently the communication cost among tasks and the composition process of lightpath for communication in optical gird environment. In this thesis, we propose LSOG (Leveling Selection in Optical Grid) which sets task priority after forming a hierarchical directed acyclic graph (DAG) that is optimized in optical grid environment. To determine priorities of task assignment in the same level, proposed algorithm executes the task with biggest communication cost between itself and its predecessor. Then, it considers the shortest route for communication between tasks. This process improves communication cost in scheduling process through optimizing link resource usage in optical grid environment. We compared LSOG algorithm with conventional ELSA (Extended List Scheduling Algorithm) and SCP (Scheduled Critical Path) algorithm. We could see the enhancement in overall scheduling performance through increment in CCR value and smoothing network environment.

• 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.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.5 no.1
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• pp.04-10
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• 1987

We consider a time sharing computer system with a single processor where tasks ofK different types arrive at the system according to independent time homogeneous Poisson processes from outside. A task, after given a quantum for processing, leaves the system, or changes the type and rejoins the system according to specified probabilitycs. While many existing priority time sharing models determine the priorities of tasks strictly by their service time requirements, this paper develops a new scheduling rule wherein the importances or urgencies in addition to the service time requirements of tasks are counted, by inposing an appropriate reward structure on the system. Also presented is the algorithm through which to determine the rankings of K types according to this new scheduling rule.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2235-2246
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• 1997

This paper presents an effective heuristic task scheduling algorithm for multiprocessor systems. To execute task scheduling effectively which is defined as an allocation of m's tasks onto n's processors(m > n), several problems almost at NP-hard should be cleaned up. The purpose of the task scheduling obtains the minimum execution time by mapping the tasks on a system topology or reduces the total execution time to give a minimum system topology. In order to solve this problem, in this paper, the task scheduling is done by redefining a task graph to a reconstructed task graph (RTG). An RTG is obtained by merging or copying nodes to equal the number of nodes on each level of the task graph to the number of processors of the system topology and then directly scheduled to the system topology. This method obtains a fast scheduling time and a simple scheduling method, and near-optimal execution time without executing steps such as the refinement step and the duplication step after the task scheduling.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1568-1579
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• 1996

Most of the real-time scheduling algorithms assume that all tasks are either preemptive or nonpreemptive. In this paper, we present a real-time scheduling algorithm for the more generalized task model in which each task contains both preemptive and nonpreemptive subtasks in a single processor environment. If the task set is found to be scheduling by the method of Harbour et al, it is also found to be scheduling by the proposed method. A simulation is used ti compare two methods and the result shows the maximum of 45% difference between them in their effectiveness.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4103-4121
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• 2018

Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4A
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• pp.393-401
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• 2006

Energy consumption is an important design parameter for battery-operated embedded systems. Dynamic power management is one of the most well-known low-power design techniques. This paper proposes an online realtime scheduling algorithm, which we call energy-aware realtime scheduling using slack stealing (EARSS). The proposed algorithm gives the highest priority to the task with the largest degree of device overlap when the slack time exists. Scheduling result enables an efficient power management by reducing the number of state transitions. Experimental results show that the proposed algorithm can save the energy by 23% on average compared to the DPM-enabled system scheduled by the EDF algorithm.