检索结果-内蒙古大学图书馆

Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International Conference on

作者： Priya Kumari Nitin Jain Department of Electronics and Communication Babu Banarasi Das University Lucknow Uttar Pradesh

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

Nowadays, multipath routing is performed in the Internet of Things (IoT) to provide reliable data transmission under different traffic conditions. In this research, multipath routing in IoT is performed by Fractional Coati Optimization Algorithm (FCOA). Here, the Quality of Experience (QoE)-driven data delivery is performed by considering IoT users and applications initially. The Transmission Control Protocol/Internet Protocol (TCP/IP) networks are considered to promote the QoE of IoT users and for prioritizing applications. The data from various IoT applications is transmitted in the form of packets and Deep Long Short-Term Memory (DLSTM) is used to perform QoE-driven packet scheduling from the packets. The multipath routing is effectuated by the FCOA by considering fitness parameters, namely energy and delay. Furthermore, the multipath routing performance of FCOA is validated by comparing the performance with existing methods. Here, the FCOA attained superior performance with residual energy and delay of 0.433J, and 0.744mS.

关键词： scheduling algorithms Scalability Heuristic algorithms TCPIP Routing Routing protocols Delays

来源：评论

学校读者我要写书评

暂无评论

DQN and Heuristic Precoding-aware scheduling in Cell-free mMIMO Networks

DQN and Heuristic Precoding-aware Scheduling in Cell-free mM...

引用

IEEE Conference on Wireless Communications and Networking

作者： Adam Girycki Md Arifur Rahman Sofie Pollin IS-Wireless Pulawska Plaza Piaseczno Poland Department of Electrical Engineering KU Leuven Belgium

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

We propose a deep Q-Learning (DQN) and heuristic-based radio resource scheduling (RRS) algorithms, which determine serving access points (APs), for maximum ratio transmission (MRT) precoder in the cell-free massive multiple-input multiple-output (CF mMIMO) networks. We show that, DQN-based algorithm yields up to 6% higher sum spectral efficiency (SE) than the heuristic and the reinforcement learning based algorithms for MRT precoder, but the heuristic algorithm yields 1000 times shorter computation time than the DQN-based algorithm. Thus, the low complexity MRT heuristic algorithms are the trade off between the performance and the cost.

关键词： Q-learning Costs Spectral efficiency scheduling algorithms Heuristic algorithms Noise Interference

来源：评论

学校读者我要写书评

暂无评论

An Efficient Hybrid Artificial Bee Colony and Fibonacci Indicator Algorithm for the Resource-Constrained Project scheduling Problem

SSRN

引用

SSRN 2024年

作者： Etminaniesfahani, Alireza Gu, Hanyu School of Mathematical and Physical Sciences University of Technology Sydney 15 Broadway Ultimo SydneyNSW2007 Australia

The Artificial bee colony (ABC) is a widely used metaheuristic optimisation algo rithm due to its simplicity, adaptability, and efficiency. However, it has a notable drawback with a limited local search capability. ABFIA, the recently proposed extension of the ABC, has shown to have a strong exploration and fast convergence and has proven effective in addressing continuous global optimisation problems. Addressing combinatorial optimisation problems using ABFIA presents several challenges. These include the need to deal with a large number of constraints, such as the precedence and resource constraints in RCPSP, as well as to explore the com plex and discrete solution space efficiently. This study proposes a new extension of ABFIA, called combinatorial ABFIA (CABFIA), to tackle RCPSP. The algorithm’s performance has been investigated on 1560 instances from the well-known library PSPLIB with 30, 60, and 120 tasks. The results indicate that the proposed Combi natorial ABFIA yields superior outcomes compared to the best-reported results in the literature and the state-of-the-art algorithms. © 2024, The Authors. All rights reserved.

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Online AI-Generated Content Request scheduling with Deep Reinforcement Learning

Online AI-Generated Content Request Scheduling with Deep Rei...

引用

IEEE Conference on Computer Communications Workshops, INFOCOM Wksps

作者： Chenglong Feng Ying Zheng X. Yuedong Fudan University Shanghai China

ISBN: (数字)9798350384475

ISBN: (纸本)9798350384482

Artificial Intelligence-Generated Content (AIGC) represents a technique that AI automatically generates various forms of content that meet the personalized requirements of humans. To offer an easy access to AIGC techniques, an edge computing system is introduced with heterogeneous computing capability to process users' text-to-image AIGC requests. For text-to-image AIGC tasks, inference steps configuration of diffusion models has a great impact on inference time and quality of generated results. Thus, it is necessary to design an online scheduling scheme to dispatch users' AIGC requests to suitable servers and tune proper inference steps for AIGC requests in order to achieve better quality of service. Based on this motivation, we define a novel online text-to-image AIGC request scheduling problem under a heterogeneous edge computing scenario with the objective of striking a balance between tardiness of AIGC requests and quality of generated results. We formulate it into an integer programming problem. Then we transform this problem into a Markov Decision Process (MDP) model and adopt a deep reinforcement learning-based algorithm to solve this online problem. Simulation results show that our approach performs better and has a strong generalization ability, compared with the baseline random policy and greedy policy.

关键词： scheduling algorithms Simulation Text to image Transforms Quality of service Deep reinforcement learning Heterogeneous networks

来源：评论

学校读者我要写书评

暂无评论

scheduling with Obligatory Tests

arXiv

引用

arXiv 2024年

作者： Dogeas, Konstantinos Erlebach, Thomas Liang, Ya-Chun Department of Computer Science Durham University United Kingdom Data Science Institute Columbia University United States

Motivated by settings such as medical treatments or aircraft maintenance, we consider a scheduling problem with jobs that consist of two operations, a test and a processing part. The time required to execute the test is known in advance while the time required to execute the processing part becomes known only upon completion of the test. We use competitive analysis to study algorithms for minimizing the sum of completion times for n given jobs on a single machine. As our main result, we prove using a novel analysis technique that the natural 1-SORT algorithm has competitive ratio at most 1.861. For the special case of uniform test times, we show that a simple threshold-based algorithm has competitive ratio at most 1.585. We also prove a lower bound that shows that no deterministic algorithm can be better than √2-competitive even in the case of uniform test times. Copyright © 2024, The Authors. All rights reserved.

关键词： scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Rule-Based scheduling for MPARs Performing Sensing and Communications

Rule-Based Scheduling for MPARs Performing Sensing and Commu...

引用

Technologies for Defense and Security (TechDefense), IEEE International Workshop on

作者： Augusto Aubry Antonio De Maio Luca Pallotta DIETI University of Naples “Federico II” Napoli Italy Department of Engineering (DiING) University of Basilicata Potenza Italy

ISBN: (数字)9798331505585

ISBN: (纸本)9798331505592

Multifunction phased array radar (MPAR) is capable of performing sensing and communications by functionally grouping a phased array into tailored sub-apertures, each dedicated to a distinct task. Because of limited available resources, such as bandwidth, power aperture product, and time, it is important to properly allocate them to each sub-aperture. This article examines a rule-based task scheduling algorithm wherein communication (COM) looks are employed to fill the vacant time left by the radar tasks that are allocated first (namely, volume and cued search, update and confirmation tracking). The allocation of looks is carried out for each time slot based on task priorities; however, some tasks (i.e., volume, cued, and COM) are executed in parallel when the available bandwidth and power-aperture product (PAP) permit. Simulations conducted in scenarios demonstrate the validity of the proposed allocation strategy in terms of bandwidth utilization and time occupancy.

关键词： Phased arrays scheduling algorithms Simulation Bandwidth Radar Radar tracking scheduling Sensors Resource management Security

来源：评论

学校读者我要写书评

暂无评论

CHESS: Concurrent Charging with Efficient Phase scheduling

CHESS: Concurrent Charging with Efficient Phase Scheduling

引用

International Conference on Parallel and Distributed Systems (ICPADS)

作者： Dié Wu Chenglong Zhang Jingwen Li Tang Liu Kun She Jianhong Zhao University of Electronic Science and Technology of China Chengdu Sichuan China Sichuan Normal University Chengdu Sichuan China Chengdu Aerospace Communication Device Company Limited Chengdu Sichuan China

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Concurrent wireless charging offers significant performance improvements for Wireless Rechargeable Sensor Networks (WRSNs). However, wave interference, arising from interactions between electromagnetic waves from multiple chargers, disrupts this process. This results in uneven power distribution, potentially leading to significantly attenuated or even negligible energy reception at certain locations. This paper addresses this challenge by introducing the Concurrent cHarging with Efficient phaSe scheduling (CHESS) problem. CHESS maximizes the energy received by critical sensors through a novel on-demand phase scheduling approach. To achieve this, we propose a practical charging model with charger phases and wave interference effects. Subsequently, a charger grouping algorithm reduces computational complexity, followed by a phase vector searching algorithm to identify optimal phases for maximizing sensor energy reception. Finally, a phase scheduling algorithm enables dynamic adaptation to the evolving energy demands. Simulations show significant efficiency improvements, outperforming baseline algorithms by an average of ${8 9. 8 \%}$

关键词： Wireless communication Adaptation models Wireless sensor networks scheduling algorithms Heuristic algorithms Computational modeling Power distribution Interference Dynamic scheduling Vectors

来源：评论

学校读者我要写书评

暂无评论

MJSCHED: A Moldable Job scheduling Algorithm in Heterogeneous Resource Environment

MJSCHED: A Moldable Job Scheduling Algorithm in Heterogeneou...

引用

International Conference on Computer and Communications (ICCC)

作者： Tianhai Zhao Zichen Yang Yunlan Wang Jianhua Gu Zhengxiong Hou School of Computer Science Northwestern Polytechnical University Xi'an China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

Moldable jobs have the ability to dynamically adjust their resource requirements before execution, offering greater flexibility compared to rigid jobs that allocate fixed resources. Currently, most resource management systems do not fully consider the resource requirements of moldable jobs, and few scheduling algorithms address the scheduling of such jobs, especially those requiring both CPU and GPU resources. In this paper, we propose a moldable job backfill algorithm(MJSched) that dynamically adjusts job resource allocation to reduce turnaround time. First, a resource allocation strategy that minimizes turnaround time is applied to jobs at the head of the waiting queue. We utilize a greedy algorithm and a genetic algorithm to construct the set of backfill jobs, determine the computational nodes, and allocate the number of tasks for these jobs. Furthermore, a profit-first remaining resource scheduling strategy is proposed. We implement the Slurm scheduling plug-in based on our moldable job scheduling algorithm to support moldable job scheduling in heterogeneous resource environments. Simulation experiments demonstrate that our MJSched-GA algorithm effectively reduces both average job turnaround time and average job waiting time by 15.7%-22% and 18.8%-26.2% respectively, while improving cluster resource utilization by 8%-14 %.

关键词： Greedy algorithms scheduling algorithms Heuristic algorithms High performance computing Clustering algorithms Graphics processing units Dynamic scheduling Genetics Resource management Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Assessment of Real time scheduling Strategies on RTOS

Assessment of Real time Scheduling Strategies on RTOS

引用

Intelligent Systems and Machine Learning Conference (ISML)

作者： Dhruva R. Rinku M. AshaRani Dept. of ECE CVR College of Engineering Hyderabad India Dept. of ECE JNTUH Hyderabad India

ISBN: (数字)9798350343878

ISBN: (纸本)9798350343885

This paper presents a comparative study of well-known real time schedulers, Earliest Deadline First (EDF) and the Rate Monotonic (RM) schedulers with the objective to evaluate their performance and suitability for real-time embedded applications on FreeRTOS. Synthetic tasks were developed to simulate real-world scenarios. Performance metrics, including average wait time, number of context switches, and CPU utilization, are then employed to assess the effectiveness of the schedulers. Results demonstrate that EDF outperforms RM in terms of deadline miss ratio, particularly under high system load. EDF also tends to minimize average wait time; however, it may result in a higher number of context switches. In contrast, RM exhibits higher average wait time but generally has fewer context switches. It is noteworthy that the difference between EDF and RM becomes less significant for periodic tasks with deadlines equal to their period, thereby increasing the performance dependability on the total number of tasks that are to be scheduled. The findings aim to assist system designers in making informed decisions when selecting a suitable scheduling algorithm for their real-time applications.

关键词： Embedded systems scheduling algorithms Switches Machine learning Dynamic scheduling Real-time systems Synchronization Resource management Kernel Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

Cloud Computing Task scheduling Strategy Based on Improved Ant Colony Optimization (ACO) Algorithm

Cloud Computing Task Scheduling Strategy Based on Improved A...

引用

IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Jiaxin Lu Aiguo Teng Junjie Zha Li Shen Zhongxing Wang State Grid Jiangsu Electric Power Co. Ltd Information and Telecommunication Branch Nanjing China Beijing China-Power Information Technology Co. Ltd Beijing China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

The rapid development of cloud computing technology has spawned a plethora of complex applications, leading to an increasing demand for efficient task scheduling algorithms. Traditional task scheduling algorithms have certain limitations in resource allocation and load balancing, making it difficult to fully adapt to the dynamic and evolving cloud computing environment. In order to enhance the efficiency of task scheduling, this study investigates a cloud computing task scheduling strategy based on an improved Ant Colony Optimization (ACO) algorithm. By refining the ant colony algorithm, this study proposes specific optimization schemes in three aspects: initialization of pheromones, selection probability of virtual machines, and pheromone updating. Leveraging the strengths of Particle Swarm Optimization (PSO), a hybrid optimization strategy (PSO _ ACO) is constructed. Simulation experiments demonstrate that this improved algorithm exhibits satisfactory performance in terms of task scheduling execution time, load balancing, and resource utilization, offering a novel solution for task management in cloud computing environments.

关键词： Cloud computing Ant colony optimization scheduling algorithms Heuristic algorithms Load management scheduling Virtual machines Resource management Particle swarm optimization Optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：