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检索条件"主题词=Scheduling algorithms"

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A Structure-Aware DAG scheduling and Allocation on Heterogeneous Multicore Systems

A Structure-Aware DAG Scheduling and Allocation on Heterogen...

引用

International Symposium on Industrial Embedded Systems

作者： Yiyang Gao Huixuan Yi Haoran Chen Xinwei Fang Shuai Zhao School of Computer Science and Engineering Sun Yat-sen University China Department of Computer Science University of York UK

ISBN: (数字)9798350388633

ISBN: (纸本)9798350388640

With the ever-increasing complexity of real-time applications, heterogeneous architectures are often applied, with tasks modelled as a Direct Acyclic Graph (DAG) to reflect their execution dependency. However, existing methods assign node priority based on a single node characteristic (e.g., execution time), which cannot leverage the DAG structure to improve performance. In addition, the allocation methods solely consider the ready nodes, which neglects their impact on the upcoming nodes, prolonging the DAG makespan. This paper introduces a novel DAG scheduling algorithm for heterogeneous real-time systems that overcomes the limitations of existing methods. First, a novel node-level priority assignment is proposed that fully exploits the DAG structure to enhance the timing performance. Then, an allocation is constructed that speeds up the execution of high-priority nodes, with upcoming nodes taken into account. The experimental results demonstrate that the proposed method outperforms the existing one up to 14.35% in the DAG makespan.

关键词： Job shop scheduling Embedded systems scheduling algorithms Multicore processing Focusing Real-time systems Timing Resource management Optimization Periodic structures

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Real-Time Multi-Service Adaptive Resource scheduling Algorithm Based on QoE

Real-Time Multi-Service Adaptive Resource Scheduling Algorit...

引用

International Conference on Information, Communication and Networks (ICICN)

作者： Wanqing Li Shufeng Li Feng Hu Fangfang Yin Communication University of China Beijing China

ISBN: (数字)9798350355802

ISBN: (纸本)9798350355819

In the modern network environment, the popularity of real-time multimedia services such as video conferencing, online games and real-time streaming media puts forward higher requirements for efficient scheduling of network resources. Since these services are highly sensitive to QoS (Quality of Service) parameters such as latency, jitter, bandwidth, and packet loss rate, ensuring the Quality of Experience (QoE) becomes a key issue. This paper mainly focuses on the research and implementation of Q-MPSA (Q-Network-based Multi-layer Perceptron scheduling Algorithm), aiming at the realization of intelligent scheduling strategies. Optimize QoE in a multi-service environment.

关键词： scheduling algorithms Packet loss Quality of service Streaming media Jitter Real-time systems scheduling Quality of experience Multimedia communication Videoconferences

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A Fair scheduling Algorithm and Schedulability Analysis for Performance Asymmetric Multiprocessors

A Fair Scheduling Algorithm and Schedulability Analysis for ...

引用

IEEE International Conference on Industrial Technology (ICIT)

作者： Peng Wu Feihang Jin Tao Yan Institute of Big Data Science and Industry Shanxi University Taiyuan China School of Computer and Information Technology Shanxi University Taiyuan China Institute of Big Data Science and Industry School of Computer and Information Technology Taiyuan China

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

We propose a new scheduling policy for performance asymmetric multiprocessors that have identical instruction sets but different processing speeds. The difference between it and the original Pfair scheduling is that when selecting scheduling parameters such as the pseudo deadline of the subtask and selecting the processor when running the highest priority subtask, it can be aware of the performance asymmetry of the underlying processor. In addition, we also propose a sufficient schedulability test for Pfair scheduling on performance asymmetric multiprocessors.

关键词： Schedules Job shop scheduling Processor scheduling scheduling algorithms Instruction sets Partitioning algorithms Time factors

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Joint Optimization for Routing and scheduling Time-Triggered Flows in Time-Sensitive Networks

Joint Optimization for Routing and Scheduling Time-Triggered...

引用

Natural Language Processing (ICNLP), International Conference on

作者： Haowei Liu Wujun Yang Zhixian Chang Dept. School of Communication and Information Engineering Xi’an University of Posts and Telecommunications Xi’an China

ISBN: (数字)9798350349115

ISBN: (纸本)9798350349122

Time-Sensitive Networks (TSN) use global Time-Triggered (TT) transport scheduling to provide deterministic communication. However, current scheduling approaches often only use scheduling constraints to determine the design space of system implementations, ignoring the interdependencies between routing and scheduling issues. Such strategies limit the ability of global scheduling for time-sensitive network communications. To this end, this paper proposes a heuristic scheduling algorithm based on a genetic algorithm, which first computes scheduling priority weights based on the deadlines, periods, and sizes of the flows, and then combines routing and scheduling constraints to generate a static global schedule using the joint constraints in a single step. Compared to methods that use only fixed routing, the method in this paper increases the solution space of the scheduling problem under joint routing and scheduling constraints.

关键词： Schedules Processor scheduling scheduling algorithms Network topology Routing scheduling System implementation Optimization Genetic algorithms Sorting

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Optimal scheduling Algorithm of Distributed Energy Resources in Virtual Power Plant Based on Cloud Computing

Optimal Scheduling Algorithm of Distributed Energy Resources...

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Telecommunications and Power Electronics (TELEPE), International Conference on

作者： Peikai Li Lianrong Pan Jiayi Yang Jiaan Li Yuan Fu Electric Power Dispatching and Control Center Guangxi Power Grid Co. Ltd. Nanning Guangxi China Laibin Power Supply Bureau of Guangxi Power Grid Co. Ltd Laibin Guangxi China

ISBN: (数字)9798350369212

ISBN: (纸本)9798350380002

The purpose of this study is to propose an optimal scheduling algorithm for Distributed Energy Resources (DER) of virtual power plants based on cloud computing, in order to meet the growing energy demand and complex energy system management challenges. The algorithm uses the flexible computing and big data processing capabilities of the cloud computing platform to achieve real-time scheduling and optimization of DER, with the goal of maximizing system profit and energy efficiency. In the aspect of algorithm design, this study combines DER modeling, energy demand modeling and optimal scheduling strategy design, and proposes an adaptive and flexible virtual power plant algorithm. Through the experimental verification, this study found that the algorithm has excellent performance in system profit, energy efficiency and scheduling response speed, and has obvious advantages compared with the traditional scheduling algorithm. In addition, the stability analysis results show that the algorithm can achieve more stable energy scheduling and management, which provides a reliable guarantee for the stable operation of the energy system. To sum up, the DER optimal scheduling algorithm of virtual power plant based on cloud computing has important theoretical and practical significance in the energy field, and provides an effective solution to improve the efficiency and reliability of the energy system.

关键词： Cloud computing scheduling algorithms Computational modeling Optimal scheduling Virtual power plants Reliability theory scheduling Stability analysis Real-time systems Energy efficiency

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Optimized Heuristic Technique for Task scheduling in Secure Cloud Storage Environment

Optimized Heuristic Technique for Task Scheduling in Secure ...

引用

International Conference on System Modeling & Advancement in Research Trends (SMART)

作者： S. Maheshwari J. Anitha Ruth Department of Computer Science SRMIST A.M. Jain College Vadapalani Chennai Department of Master of Computer Application Faculty of Science and Humanities Vadapalani Chennai

ISBN: (数字)9798350380583

ISBN: (纸本)9798350380590

Cloud computing is a highly scalable and frequently used expertise in today's rapidly evolving information and computer landscape. It runs on the payper-use, remote access, Internet-based, and on demand ideas, offering consumers a shared pool of programmable resources. However, as the number of user requests grows, efficient task scheduling and resource allocation have become critical criteria for effective workload balancing among cloud resources. It consequently improves overall cloud system performance and offers a new way to deliver services in distributed systems, paving the way for the execution of scientific applications. scheduling and processing millions of activities using Cloud resources in a lucrative manner with minimal computing time is an attractive study area. Current scheduling algorithms ignore dependent and independent jobs. To overcome this drawback, we anticipate a new dignified technique called the Optimized heuristic Min-Min algorithm, which is stimulated by the Min-Min algorithm for task scheduling and focuses on the concern of dependent and independent tasks, as well as the parallel processing of independent tasks, which directly results in profit by minimizing computation time. This study aims to produce optimal results by minimizing completion time and maximizing resource utilization, leading to higher throughput. Kerberos authentication service is implementing for cloud data storage security. Kerberos used in this work for creating tickets and granting them to every user in order to provide high security.

关键词： Cloud computing scheduling algorithms Heuristic algorithms System performance Parallel processing Throughput scheduling Security Resource management Secure storage

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Multi-UAV continuous power inspection scheduling algorithm based on NSGA-III

Multi-UAV continuous power inspection scheduling algorithm b...

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Intelligent Robotics and Automatic Control (IRAC), International Conference on

作者： Manshu Liang Wenbin Wu Weihao Zhang Shuning Yao Electric Power Science Research Institute State Grid Fujian Electric Power Co. Ltd Fuzhou China Electric Power Science Research Institute of State Grid Fujian Electric Power Co. Ltd Fuzhou China

ISBN: (数字)9798350389807

ISBN: (纸本)9798350389814

This paper focuses on addressing the optimization scheduling problem of multi-UAV power inspection tasks. In the context of power inspections, it is often not feasible for a single UAV to complete the inspection due to limitations such as power endurance, UAV hardware constraints, and task settings. Consequently, multiple UAVs are required to perform inspections in a continuous manner. The study models the complex scenario of power line inspection as a multi-objective optimization problem, considering various risk factors associated with UAV operations. By examining these risks, the study proposes a solution based on the Non-dominated Sorting Genetic Algorithm III (NSGA-III) algorithm. The proposed approach aims to minimize both the total risk and the maximum risk faced by UAVs during the inspection process. Comparative experiments are conducted to validate the effectiveness of the proposed algorithm. The results demonstrate that, compared to traditional rule-based methods, the NSGA-III algorithm significantly reduces both total risk and maximum risk, ensuring efficient and safe power inspection. Furthermore, the study also considers the failure continuation case, where the remaining UAVs can effectively take over and complete the inspection tasks in case of failure of one UAV. This contributes to the development of more reliable and robust UAV-based power inspection techniques.

关键词： scheduling algorithms Inspection Autonomous aerial vehicles Stability analysis scheduling Hardware Reliability Optimization Robots Sorting

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GNN-Based QoE Optimization for Dependent Task scheduling in Edge-Cloud Computing Network

GNN-Based QoE Optimization for Dependent Task Scheduling in ...

引用

IEEE Conference on Wireless Communications and Networking

作者： Yani Ping Kun Xie Xiaohong Huang Chengcheng Li Yasheng Zhang Network and Information Center Beijing University of Posts and Telecommunications Beijing China The 54th Research Institute of CETC Shijiazhuang China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

With the increasing diversity of user demands for network resources, efficient and flexible task scheduling schemes have gained greater importance. Given that existing works about dependent task scheduling primarily focus on optimizing QoS objectives without considering the impact of user preferences on decision results, and the majority of prior research neglects the underlying relationships among dependent tasks. In this paper, we introduce a Graph Neural Networks (GNN) based dependent task scheduling algorithm (GDTA) to enhance user satisfaction and propose a QoE model to assess user-centered quality of experience. This novel approach incorporates GNN for the purpose of generating embeddings for tasks and networks, leveraging its inherent capability in extracting graph-based features. Compared with baseline algorithms across diverse task parallelisms and network topologies, our method achieves higher QoE scores and shows superior stability and generalization on unseen graph datasets.

关键词： Network topology scheduling algorithms Quality of service Parallel processing Feature extraction Graph neural networks Stability analysis

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Power-Aware Test scheduling for Memory BIST

Power-Aware Test Scheduling for Memory BIST

引用

IEEE International Test Conference

作者： Albert Au Michał Kçpiński Makary Orczyk Artur Pogiel Siemens EDA Ottawa Canada Siemens EDA Poznań Poland Poznań University of Technology Poznań Poland

ISBN: (数字)9798331520137

ISBN: (纸本)9798331520144

An increasing number of embedded memory instances, despite lowering the power supply voltage and technology node size, leads to higher power dissipation during the memory test phase when manufacturing a System-on-Chip (SoC). Commonly used manual memory test scheduling techniques need to be replaced with more systematic approaches. The objective is to minimize the test time through concurrent memory testing, resulting in maximization of the dissipated power, but in the way the given power budget is not exceeded. The paper comprises two topics. Firstly, it presents a toolchain aimed at a thorough monitoring of the power dispersed by memory instances and associated Memory Built-In Self-Test (MBIST) instruments. Secondly, several algorithms are proposed that optimize the memory test scheduling for a commercial Design-for-Test (DFT) tool.

关键词： Schedules Job shop scheduling Systematics scheduling algorithms Instruments Voltage Built-in self-test System-on-chip Test pattern generators Monitoring

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Multi-Objective Concurrent Kernel scheduling for Multi-GPU Systems

Multi-Objective Concurrent Kernel Scheduling for Multi-GPU S...

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Iranian Conference on Electrical Engineering (ICEE)

作者： Negar Baradar Alizadeh Mahmoud Momtazpour Department of Computer Engineering Amirkabir University of Technology Tehran Iran

ISBN: (数字)9798350376340

ISBN: (纸本)9798350376357

GPUs are now being widely used in many applications to speed up the computations. Due to its unique architecture, GPUs are well suited to run embarrassingly parallel applications such as deep learning and big data analysis. However, GPUs are power hungry devices, and many applications are not able to fully utilize the resources of a GPU, resulting in energy wastage in multi-GPU systems. To tackle this challenge, recent advancement has made it possible to run multiple kernels concurrently on a single GPU to share its resources. This however comes with a performance penalty due to the interference of concurrent kernels while competing over shared resources. In the presence of such impacts, mapping and scheduling of multiple kernels on multiple GPUs in order to fully utilize the GPUs, minimize the energy consumption, and reduce interference and performance degradation is challenging. In this paper, we propose a multi-objective kernel scheduling approach for multi-GPU systems, which considers both energy consumption and performance and supports concurrent kernel execution. To solve the scheduling problem, due to its large solution space, a GA-based scheduler called CK-GA has been used that can achieve desirable solutions at a reasonable pace. We also propose a heuristic scheduling algorithm called CK-HEFT based on the well-known HEFT algorithm for concurrent kernel execution on shared GPUs. Experimental results on several multi-GPU architectures show that the proposed CK-GA scheduler has obtained more than 14% improvement in performance, 30% improvement in quality of service and more than 18% improvement in energy consumption on average compared to similar approaches.

关键词： Energy consumption Costs scheduling algorithms Heuristic algorithms Graphics processing units Quality of service Interference

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