• Journal of KIISE:Computer Systems and Theory
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• v.30 no.2
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• pp.68-77
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• 2003

The Least-Laxity First(or LLF) scheduling algorithm assigns the highest priority to a task with the least laxity, and has been proved to be optimal for a uni-processor and sub-optimal for a multi-processor. However, this algorithm Is Impractical to implement because laxity tie results in the frequent context switches among tasks. In this paper, a Modified Least-Laxity First on Multiprocessor(or MLLF/MP) scheduling algorithm is proposed to solve this problem, i.e., laxity tie results in the excessive scheduling overheads. The MLLF/MP is based on the LLF, but allows the laxity inversion. MLLF/MP continues executing the current running task as far as other tasks do not miss their deadlines. Consequently, it avoids the frequent context switches. We prove that the MLLF/MP is also sub-optimal in multiprocessor systems. By simulation results, we show that the MLLF/MP has less scheduling overheads than LLF.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.177-184
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• 2015

This paper proposes a minimum-power scheduling scheme of real-time parallel tasks while meeting deadlines of the real-time tasks on DVFS-enabled multicore processors. The proposed scheme first finds a floating number of processing cores to each task so that the computation load of all processing cores would be equalized. Next the scheme translates the found floating number of cores into a natural number of cores while maintaining the computation load of all cores unchanged, and allocates the translated natural number of cores to the execution of each task. The scheme is designed to minimize the power consumption of the frequency-sharing multicore processor operating with the same processing speed at an instant time. Evaluation shows that the scheme saves up to 38% power consumption of the previous method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.38-46
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• 2011

The OPRoS (Open Platform for Robotic Service) framework provides uniform operating environment for service robots. As an OPRoS-based service robot has to support real-time as well as non-real-time applications, application of Windows NT kernel based operating system can be restrictive. On the other hand, various benefits such as rich library and device support and abundant developer pool can be enjoyed when service robots are built on Windows NT. The paper presents a user-mode component scheduler of OPRoS, which can provide near real-time scheduling service on Windows NT based on the restricted real-time features of Windows NT kernel. The component scheduler thread with the highest real-time priority in Windows NT system acquires CPU control. And then the component scheduler suspends and resumes each periodic component executors based on its priority and precedence dependency so that the component executors are scheduled in the preemptive manner. We show experiment analysis on the performance limitations of the proposed scheduling technique. The analysis and experimental results show that the proposed scheduler guarantees highly reliable timing down to the resolution of 10ms.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.4
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• pp.26-36
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• 2000

This paper proposes a neural network algorithm for real-time multiprocessor scheduling problem. The proposed algorithm is developed base on Hopfield neural network for a benefit of parallel processing, in order to finish a requested task within a deadline time. To compare the performance of the proposed algorithm, we used EDA and LLA algorithm that has studied real-time multiprocessor scheduling before. The proposed algorithm is implemented hardware using VHDL.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.3
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• pp.128-135
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• 2010

Recently complexity of embedded software cause to be used real-time operating system (RTOS) to implement various functions in the embedded system. And also, according to requirement of complex functions in embedded systems, the number as well as complexity of tasks get increased continuously. In case that many tasks collaborated in a microprocessor, context switching time between tasks is a overhead waisting a CPU resource. Therefore the time of task context switching is an important factor that affects performance of RTOS. In this paper, we concentrate on the improvement of task context switch for reducing overhead and achieving fast response time in RTOS. To achieve these goal, we suggest multiple register files and task context switching algorithm. By reducing the context switch overhead, we try to ease scheduling and assure fast response times in multitasking environment. As a result, the context switch overhead decreased by 8~16% depend on the number of register files, and some task set which are not schedulable with single register file are schedulable due to that decrease with multiple register files.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1741-1751
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• 2007

The imprecise computation technique ensures that all time-critical tasks produce their results before their deadlines by trading off the quality of the results for the computation time requirements of the tasks. In the imprecise computation, most scheduling problems of satisfying both 0/1 constraints and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. In the previous studies, the reasonable strategies of scheduling tasks with the 0/1 constraints on uniprocessors and multiprocessors for minimizing the total error are proposed. But, these algorithms are all off-line algorithms. Then, in the on-line scheduling, NORA(No Off-line tasks and on-line tasks Ready upon Arrival) algorithm can find a schedule with the minimum total error. In NORA algorithm, EDF(Earliest Deadline First) strategy is adopted in the scheduling of optional tasks. On the other hand, for the task system with 0/1 constraints, NORA algorithm may not suitable any more for minimizing total error of the imprecise tasks. Therefore, in this paper, an on-line algorithm is proposed to minimize total error for the imprecise real-time task system with 0/1 constraints. This algorithm is suitable for the imprecise on-line system with 0/1 constraints. Next, to evaluate performance of this algorithm, a series of experiments are done. As a consequence of the performance comparison, it has been concluded that IOSMTE(Imprecise On-line Scheduling to Minimize Total Error) algorithm proposed in this paper outperforms LOF(Longest Optional First) strategy and SOF(Shortest Optional First) strategy for the most cases.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.7
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• pp.22-28
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• 2009

As multiprocessors have been widely adopted in embedded systems, task computation energy consumption should be minimized with several low power techniques supported by the multiprocessors. This paper proposes an energy-aware task scheduling algorithm that adopts both dynamic voltage scaling and power shutdown in multiprocessor environments. Considering the timing and energy overhead of power shutdown, the proposed algorithm performs an iterative task assignment and task ordering for multiprocessor systems. In this case, the iterative priority-based task scheduling is adopted to obtain the best solution with the minimized total energy consumption. Total energy consumption is calculated by considering a linear programming model and threshold time of power shutdown. By analyzing experimental results for standard task graphs based on real applications, the resource and timing limitations were analyzed to maximize energy savings. Considering the experimental results, the proposed energy-aware task scheduling provided meaningful performance enhancements over the existing priority-based task scheduling approaches.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.322-333
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• 2012

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability. For this reason, Radar Resource Management(RRM) becomes new challenging issue. RRM is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed a rule-based scheduling algorithm and Simulated Annealing(SA) based scheduling algorithm, which are alternatively selected and applied to beam scheduler according radar load status in real-time. The performance of the proposed algorithm was evaluated on the multi-function radar scenario. As a result, we showed that our proposed algorithm can process a lot of beams at the right time with real time capability, compared with applying only rule-based scheduling algorithm. Additionally, we showed that the proposed algorithm can save scheduling time remarkably, compared with applying only SA-based scheduling algorithm.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.311-314
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• 2003

In recent years, distributed control systems(DCS) using fieldbus such as CAN have been applied to process systems but it is very difficult to design the DCS while guaranteeing the given end-to-end constraints such as precedence constraints, time constraints, and periods and priorities of tasks and messages. This paper presents a scheduling method to guarantee the given end-to-end constraints considering aperiodic, periodic and non-real-time message and task simultaneously. The presented scheduling method is the integrated one considering both tasks executed in each node and messages transmitted via the network and is designed to be applied to a general DCS that has multiple loops with several types of constraints, where each loop consists of sensor nodes with multiple sensors, actuator nodes with multiple actuators and controller nodes with multiple tasks.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.83-93
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• 2007

In this paper, we address a power-aware scheduling algorithm for a mixed real-time system which consists of periodic and sporadic tasks, each of which is characterized by its minimum period, worst-case execution requirement and deadline. We propose a dynamic voltage scaling algorithm called DVSMT(DVS for mixed tasks), which dynamically scales down the supplying voltage(and thus the frequency) using on-line distribution of the borrowed resources when jobs complete while still meeting their deadlines. With this scheme, we could reduce more energy consumption. As the proposed algorithm can be easily incorporated with RTOS(Real-Time Operating System), it is applicable for handhold devices and sensor network nodes that use a limited battery power. Simulation results show that DVSMT saves up 60% more than the existing algorithms both in the periodic-task and mixed-task systems.