• Title/Summary/Keyword: dynamic task scheduling

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A rule-based scheduling system for automated machining

  • Ahn, Jaekyoung
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1992.04b
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    • pp.249-257
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    • 1992
  • An automated machining system involves concurrent use of manufacturing resources, alternative process plans, and flexible routings. High investment in the installation of automated facilities requires an efficient scheduling system that is able to allocate the resources specified for operations over a scheduling horizon. The primary emphasis of this paper is to generate schedules that accurately reflect details of the automated environment and the objectives stated for the system. In this paper, a scheduling algorithm for automated machining is presented. Using the previous simulation research for this topic, a rule-based scheduling system is constructed. An architecture for an intelligent scheduling system is proposed, and the system has a high potential to provide efficient schedules based on the task-specific knowledge for the dynamic scheduling environment

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A Dynamic Voltage Scaling Algorithm for Low-Energy Hard Real-Time Applications using Execution Time Profile (실행 시간 프로파일을 이용한 저전력 경성 실시간 프로그램용 동적 전압 조절 알고리즘)

  • 신동군;김지홍
    • Journal of KIISE:Computer Systems and Theory
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    • v.29 no.11
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    • pp.601-610
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    • 2002
  • Intra-task voltage scheduling (IntraVS), which adjusts the supply voltage within an individual task boundary, is an effective technique for developing low-power applications. In this paper, we propose a novel intra-task voltage scheduling algorithm for hard real-time applications based on average-case execution time. Unlike the conventional IntraVS algorithm where voltage scaling decisions are based on the worst-case execution cycles, tile proposed algorithm improves the energy efficiency by controlling the execution speed based on average-case execution cycles while meeting the real-time constraints. The experimental results using an MPEG-4 decoder program show that the proposed algorithm reduces the energy consumption by up to 34% over conventional IntraVS algorithm.

Dynamic Voltage Scaling Technique Considering Application Characteristics (응용 프로그램 특성을 고려한 동적 전압 조절 기법)

  • Cho, Young-Jin;Chang, Nae-Hyuck
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.12
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    • pp.96-104
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    • 2009
  • In the real system environments, the performance of the application is not linearly proportional to the clock frequency of the microprocessor, in contrast to the general assumption of conventional dynamic voltage scaling. In this paper, we analytically model the relation between the performance of the application and the clock frequency of the microprocessor, and introduce the energy-optimal scheduling algorithm for a task set with distinct application characteristics. In addition, we present a theorem for the energy-optimal scheduling, which the derivative of the energy consumption with respect to the execution time should be the same for all the tasks. The proposed scheduling algorithm always generates the energy-optimal scaling factor thanks to the theorem for energy-optimal scheduling. We achieved about 7% additional energy reduction in the experiments using synthetic task sets.

Time-Efficient Voltage Scheduling Algorithms for Embedded Real-Time Systems with Task Synchronization (태스크 동기화가 필요한 임베디드 실기간 시스템에서 시간-효율적인 전압 스케쥴링 알고리즘)

  • Lee, Jae-Dong;Kim, Jung-Jong
    • Journal of Korea Multimedia Society
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    • v.13 no.1
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    • pp.30-37
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    • 2010
  • Many embedded real - lime systems have adopted processors supported with dynamic voltage scal-ing(DVS) recently. Power is one of the important metrics for Optimization in the design and operation of embedded real-time systems. We can save considerable energy by using slowdown of processor sup-ported with DVS. In this paper, we improved the previous algorithm at a point of view of time complexity to calculate task slowdown factors for an efficient energy consumption in embedded real-time systems with task synchronization. We grasped the properties of the previous algorithm having $O(n^{2})$ time complexity through mathematical analysis and s simulation. Using its properties we proposed the improved algorithms with O(nlogn) and O(n) time complexity which have the same performance as the previous algorithm has.

Kernel Thread Scheduling in Real-Time Linux for Wearable Computers

  • Kang, Dong-Wook;Lee, Woo-Joong;Park, Chan-Ik
    • ETRI Journal
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    • v.29 no.3
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    • pp.270-280
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    • 2007
  • In Linux, real-time tasks are supported by separating real-time task priorities from non-real-time task priorities. However, this separation of priority ranges may not be effective when real-time tasks make the system calls that are taken care of by the kernel threads. Thus, Linux is considered a soft real-time system. Moreover, kernel threads are configured to have static priorities for throughputs. The static assignment of priorities to kernel threads causes trouble for real-time tasks when real-time tasks require kernel threads to be invoked to handle the system calls because kernel threads do not discriminate between real-time and non-real-time tasks. We present a dynamic kernel thread scheduling mechanism with weighted average priority inheritance protocol (PIP), a variation of the PIP. The scheduling algorithm assigns proper priorities to kernel threads at runtime by monitoring the activities of user-level real-time tasks. Experimental results show that the algorithms can greatly improve the unexpected execution latency of real-time tasks.

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An Improved Dynamic Quantum-Size Pfair Scheduling for the Mode Change Environments (Mode Change 환경을 위한 개선된 동적 퀀텀 크기 Pfair 스케줄링)

  • Cha, Seong-Duk;Kim, In-Guk
    • Journal of Digital Contents Society
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    • v.8 no.3
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    • pp.279-288
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    • 2007
  • Recently, Baruah et. al. proposed an optimal Pfair scheduling algorithm in the real-time multiprocessor system environments, and several variants of it were presented. All these algorithms assume the fixed unit quantum size. However, under Pfair based scheduling algorithms that are global scheduling technique, quantum size has direct influence on the scheduling overheads such as task switching and cache reload. We proposed a method for deciding the optimal quantum size[2] and an improved method for the task set whose utilization e is less than or equal to $e\;{\leq}\;p/3+1$[3]. However, these methods use repetitive computation of the task's utilization to determine the optimal quantum size. In this paper, we propose a more efficient method that can determine the optimal quantum size in constant time.

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An Engine for DRA in Container Orchestration Using Machine Learning

  • Gun-Woo Kim;Seo-Yeon Gu;Seok-Jae Moon;Byung-Joon Park
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.126-133
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    • 2023
  • Recent advancements in cloud service virtualization technologies have witnessed a shift from a Virtual Machine-centric approach to a container-centric paradigm, offering advantages such as faster deployment and enhanced portability. Container orchestration has emerged as a key technology for efficient management and scheduling of these containers. However, with the increasing complexity and diversity of heterogeneous workloads and service types, resource scheduling has become a challenging task. Various research endeavors are underway to address the challenges posed by diverse workloads and services. Yet, a systematic approach to container orchestration for effective cloud management has not been clearly defined. This paper proposes the DRA-Engine (Dynamic Resource Allocation Engine) for resource scheduling in container orchestration. The proposed engine comprises the Request Load Procedure, Required Resource Measurement Procedure, and Resource Provision Decision Procedure. Through these components, the DRA-Engine dynamically allocates resources according to the application's requirements, presenting a solution to the challenges of resource scheduling in container orchestration.

An Efficient DVS Algorithm for Pinwheel Task Schedules

  • Chen, Da-Ren;Chen, You-Shyang
    • Journal of Information Processing Systems
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    • v.7 no.4
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    • pp.613-626
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    • 2011
  • In this paper, we focus on the pinwheel task model with a variable voltage processor with d discrete voltage/speed levels. We propose an intra-task DVS algorithm, which constructs a minimum energy schedule for k tasks in O(d+k log k) time We also give an inter-task DVS algorithm with O(d+n log n) time, where n denotes the number of jobs. Previous approaches solve this problem by generating a canonical schedule beforehand and adjusting the tasks' speed in O(dn log n) or O($n^3$) time. However, the length of a canonical schedule depends on the hyper period of those task periods and is of exponential length in general. In our approach, the tasks with arbitrary periods are first transformed into harmonic periods and then profile their key features. Afterward, an optimal discrete voltage schedule can be computed directly from those features.

AUTOSAR : Deadline-Compliant Scheduling Method Applicable to Timing Protection Mechanisms (AUTOSAR:타이밍 보호 메커니즘 적용 가능한 마감시간 준수 스케줄링 방법)

  • Kim, Joo-Man;Kim, Seon-Jong;Kim, Byoung-Chul;Kwon, Hyeog-Soong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.103-109
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    • 2019
  • The automotive electronic system should provide a method that can be safely performed by loading a number of application programs having time constraints in several electronic control devices. In this paper, we propose a timing protection mechanism for AUTOSAR, which is a real - time operating system specification for automotive field, in order to observe the deadline of each task when scheduling real - time tasks. We propose a dynamic non-preemption algorithm to guarantee a flexible deadline for fixed priority or dynamic priority tasks, and a location where execution time can be monitored for errors, and suggest ways to implement the AUTOSAR time protection mechanism.

Performance Enhancement of On-Line Scheduling Algorithm for IRIS Real-Time Tasks using Partial Solution (부분 해를 이용한 IRIS 실시간 태스크용 온-라인 스케줄링 알고리즘의 성능향상)

  • 심재홍;최경희;정기현
    • Journal of KIISE:Computer Systems and Theory
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    • v.30 no.1
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    • pp.12-21
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    • 2003
  • In this paper, we propose an on-line scheduling algorithm with the goal of maximizing the total reward of IRIS (Increasing Reward with Increasing Service) real-time tasks that have reward functions and arrive dynamically into the system. We focus on enhancing the performance of scheduling algorithm, which W.: based on the following two main ideas. First, we show that the problem to maximize the total reward of dynamic tasks can also be solved by the problem to find minimum of maximum derivatives of reward functions. Secondly, we observed that only a few of scheduled tasks are serviced until a new task arrives, and the rest tasks are rescheduled with the new task. Based on our observation, the Proposed algorithm doesn't schedules all tasks in the system at every scheduling print, but a part of tasks. The performance of the proposed algorithm is verified through the simulations for various cases. The simulation result showed that the computational complexity of proposed algorithm is$O(N_2)$ in the worst case which is equal to those of the previous algorithms, but close to O(N) on the average.