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arXiv 2023年

作者： Khan, Muhammad Azeem Yang, Howard H. Chen, Zihan Iera, Antonio Pappas, Nikolaos DIMES Department University of Calabria CS Arcavacata di Rende Italy ZJU-UIUC Institute Zhejiang University China ISTD Pillar Singapore University of Technology and Design Singapore Department of Computer and Information Science Linköping University Sweden

Data possesses significant value as it fuels advancements in AI. However, protecting the privacy of the data generated by end-user devices has become crucial. Federated Learning (FL) offers a solution by preserving data privacy during training. FL brings the model directly to User Equipments (UEs) for local training by an access point (AP). The AP periodically aggregates trained parameters from UEs, enhancing the model and sending it back to them. However, due to communication constraints, only a subset of UEs can update parameters during each global aggregation. Consequently, developing innovative scheduling algorithms is vital to enable complete FL implementation and enhance FL convergence. In this paper, we present a scheduling policy combining Age of Update (AoU) concepts and data Shapley metrics. This policy considers the freshness and value of received parameter updates from individual data sources and real-time channel conditions to enhance FL's operational efficiency. The proposed algorithm is simple, and its effectiveness is demonstrated through simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： scheduling algorithms

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Study and analysis of various task scheduling algorithms in the cloud computing environment

Study and analysis of various task scheduling algorithms in ...

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Teena Mathew K. Chandra Sekaran John Jose Dept. of Computer Science & Engineering Rajagiri School of Engineering & Technology Kochi India Dept. of Computer Science & Engineering Rajagiri School of Engineering & Technology Surathkal India

ISBN: (纸本)9781479930814

Cloud computing is a novel perspective for large scale distributed computing and parallel processing. It provides computing as a utility service on a pay per use basis. The performance and efficiency of cloud computing services always depends upon the performance of the user tasks submitted to the cloud system. scheduling of the user tasks plays significant role in improving performance of the cloud services. Task scheduling is one of the main types of scheduling performed. This paper presents a detailed study of various task scheduling methods existing for the cloud environment. A brief analysis of various scheduling parameters considered in these methods is also discussed in this paper.

关键词： Load management Dynamic scheduling scheduling algorithms Heuristic algorithms Servers

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A java based visual tool to learn CPU scheduling algorithms

A java based visual tool to learn CPU scheduling algorithms

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Neetu Jain P. V. Suresh SOCIS IGNOU New Delhi

CPU scheduling algorithms are integral part of learning operating system. Over the years, it has been experienced that initially CS students face a lot of problems in understanding and further implementing the various scheduling algorithms. Also generating and regenerating Gantt Charts is faced with difficulties by many CS students. A visual tool or diagram has always been effective way in better learning and understanding. We developed a Java and Java Swing based application, to visually explain various scheduling algorithms. User can enter the runtime details of processes and the tool is capable of graphically showing the execution of processes inside the system using a particular scheduling algorithm. The tool is also capable of doing calculations different effectiveness criteria of an algorithm like waiting time of each process, average waiting time and turnaround time. Proposed tool has used different colors to depict processes to have much better understanding of the operations inside the system.

关键词： scheduling algorithms Operating systems Decision support systems Visualization Java Handheld computers Education

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SAUFEE: A Datacenter Task scheduling Algorithm Considering User Fairness and Energy Efficiency

SAUFEE: A Datacenter Task Scheduling Algorithm Considering U...

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Networking Systems of AI (INSAI), International Conference on

作者： Yuanlong Peng Longchuan Yan Ce Yu Wantao Liu State Grid Information & Telecommunication Branch Beijing China Chinese Academy of Sciences Institute of Information Engineering Beijing China

ISBN: (数字)9798350344660

ISBN: (纸本)9798350344677

The data center uses virtualization and isolation technologies to provide flexible and efficient services for multi-tenants. One of the most challenging aspect of resource sharing is task scheduling. During the scheduling process, it is crucial to ensure fairness in user resource usage and achieve high cluster utilization and energy efficiency. However, the heterogeneity of resources and the variations in user demands make it extremely difficult to provide an effective scheduling solution. In this paper, we propose an efficient heuristic scheduling algorithm called SAUFEE, which trades off the resource requirement of multi-tenants and cluster power consumption. First, we introduce a user fairness model, which prioritizes the tasks of users with the least resource allocation in each scheduling round, ensuring fairness among them. Next, we propose a resource utilization model to schedule user tasks to reduce resource waste. Additionally, idle machines are shut down to save overall cluster energy consumption. The simulation experiment results show that our algorithm increases the number of running tasks by 3.3% and the CPU utilization by 3.4% while ensuring fairness. Our algorithm plays an important role in improving cluster energy efficiency and user fairness.

关键词： Schedules Power demand scheduling algorithms Heuristic algorithms Clustering algorithms Reinforcement learning Energy efficiency scheduling Resource management Virtualization

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Research on Intelligent scheduling Algorithm Based on Cloud Computing

Research on Intelligent Scheduling Algorithm Based on Cloud ...

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International Conference on Computer Research and Development (ICCRD)

作者： Xiaofeng Yan Jie Zhao Jianchao Han Chongqing Medical and Pharmaceutical College Chongqing China

With the rapid development of the information age, computer technology and network technology are more and more mature, and the application of Internet technology is more and more extensive. On the basis of the gradual development and maturity of distributed computing, parallel computing and grid computing, cloud computing based on big data came into being. The core idea of cloud computing is to connect a large number of computing resources, storage resources and service resources through the network to form a resource pool, and then conduct unified scheduling and management of resources according to user needs. This paper mainly studies the resource scheduling method based on neural network and genetic algorithm to dynamically provide data centric computing service system for users, and maximize the reliability, customization and security of the services provided.

关键词： Cloud computing scheduling algorithms Heuristic algorithms Neural networks Parallel processing Information age Grid computing

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An Optimised Energy Efficient Task scheduling Algorithm based on Deep Learning Technique for Energy Consumption

An Optimised Energy Efficient Task Scheduling Algorithm base...

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International Conference on Information Systems and Computer Networks (ISCON)

作者： Jenifer Mahilraj P. Sivaram Ns Lokesh Bhisham Sharma Department of Computer Science & Engineering NPR College of Engineering Natham Tamilnadu India Department of Artificial Intelligence G H Raisoni College of Engineering Nagpur Maharashtra India Department of CSE School of Technology GITAM University Bangalore Karnataka India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

The information technology (IT) and mobile computing industries are now in the development stages of cloud computing (CC). Instead of being purchased, resources such as software, CPUs, memory, I/O hardware, and others are used and charged as needed. The massive expansion of CC necessitates enormous energy consumption, or data centers house a diverse spectrum of computers. Consequently, cloud service providers are exploring low-cost strategies for reducing energy use and carbon emissions. Therefore, work planning has garnered great attention and critical consideration about effective resources and bad energy consumption. This paper proposes a machine learning technique called short-term or Long-Term Memory (LSTM) for efficient power task scheduling to address growing carbon or energy emissions. The recommended strategy for scheduling considers the finish time or exclusive usage of a resource task, as well as the standardizing process. The Novel Black Window is used to reduce weight and improve the performance of LTSM. The simulated analysis is used to evaluate the efficiency of the LSTM-NBW in aspects of makes pan, power consumption, task completion time, and resource utilization. The findings show that the suggested model only obtained 400KWh more for the 80kB user job than the original LSTM model.

关键词： Cloud computing Energy consumption Job shop scheduling Power demand scheduling algorithms Carbon dioxide Virtual machining

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Cubesat Task scheduling Method Considering Operational Reliability

SSRN

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SSRN 2023年

作者： Zhang, Jingjing He, Chenyang Zhang, Yan Qi, Xianjun Yang, Xi School of Electrical Engineering and automation Hefei University of Technology Hefei China Anhui Province Key Laboratory of Renewable Energy Utilization and Energy Saving Hefei University of Technology Hefei China Key Lab. of Aperture Array and Space Application Hefei China

Task scheduling is an effective method to increase the value of satellite missions, which can greatly improve satellite resource management and quality of service. Based on the priority-based task scheduling model, this paper proposes a CubeSat scheduling method that takes operational reliability into account, considering the impact of scheduling results on its reliable operation. In this method, the available energy and the time window are used as scheduling resources, and the average charge state of the lithium battery and the number of task start-ups are defined as two index to measure its reliability. To meet the mission requirements and energy availability of PV and battery constraints, the scheduling model is constructed whose objective function includes mission priority and reliability index. Branch and bound (BB) method and Analytical hierarchy process (AHP) method are used to solve the scheduling problem. The example analysis compares different scheduling results and verifies the effectiveness of the proposed scheduling method. Compared with the existing methods, it comprehensively considers the mission value and operational reliability of the CubeSat, improves the energy reserve level of the CubeSat, reduces the surge current caused by the start-up of the task, and can provide guidance for its task scheduling. © 2023, The Authors. All rights reserved.

关键词： scheduling algorithms

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Model Checking for scheduling on Flight Decks of Aircraft Carriers

Model Checking for Scheduling on Flight Decks of Aircraft Ca...

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IEEE Information Technology, Networking, Electronic and Automation Control Conference

作者： Weijun Zhu Yiran Wang School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China School of Network Engineering Zhoukou Normal University Zhoukou China

scheduling carrier-based aircraft is very vital to the efficiency of tasks on the deck of an aircraft carrier, and many approaches have been proposed to solve the scheduling problem. However, no formal method available for verifying the correctness of the scheduling carrier-based aircraft. To this end, we propose a novel method for model checking scheduling tasks on decks of Aircraft Carriers (AC). First, a number of Interval Temporal Logic (ITL) formulas are employed to model the actions and the resources on a deck. Second, some other ITL formulas can be used to describe some properties which should be satisfied. As a result, the existing Model Checking (MC) interval temporal logic algorithms can be employed to verify the correctness and other properties of the scheduling carrier-based aircraft. A case study demonstrates the effectiveness of the new method. In addition, an idea about model checking scheduling algorithms of AC decks, is also pioneered.

关键词： Automation scheduling algorithms Atmospheric modeling Model checking scheduling Aircraft Task analysis

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How Workflow Engines Should Talk to Resource Managers: A Proposal for a Common Workflow scheduling Interface

arXiv

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arXiv 2023年

作者： Lehmann, Fabian Bader, Jonathan Tschirpke, Friedrich Thamsen, Lauritz Leser, Ulf Humboldt-Universität Berlin Germany Technische Universität Berlin Germany University of Glasgow United Kingdom

Scientific workflow management systems (SWMSs) and resource managers together ensure that tasks are scheduled on provisioned resources so that all dependencies are obeyed, and some optimization goal, such as makespan minimization, is achieved. In practice, however, there is no clear separation of scheduling responsibilities between an SWMS and a resource manager because there exists no agreed-upon separation of concerns between their different components. This has two consequences. First, the lack of a standardized API to exchange scheduling information between SWMSs and resource managers hinders portability. It incurs costly adaptations when a component should be replaced by a different one (e.g., an SWMS with another SWMS on the same resource manager). Second, due to overlapping functionalities, current installations often actually have two schedulers, both making partial scheduling decisions under incomplete information, leading to suboptimal workflow scheduling. In this paper, we propose a simple REST interface between SWMSs and resource managers, which allows any SWMS to pass dynamic workflow information to a resource manager, enabling maximally informed scheduling decisions. We provide an implementation of this API as an example, using Nextflow as an SWMS and Kubernetes as a resource manager. Our experiments with nine real-world workflows show that this strategy reduces makespan by up to 25.1% and 10.8% on average compared to the standard Nextflow/Kubernetes configuration. Furthermore, a more widespread implementation of this API would enable leaner code bases, a simpler exchange of components of workflow systems, and a unified place to implement new scheduling algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： scheduling algorithms

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An efficient charging scheduling scheme to enhance the wireless rechargeable sensor networks' lifespan

An efficient charging scheduling scheme to enhance the wirel...

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International Symposium on Advanced Computing and Communication (ISACC)

作者： Sk Md Abidar Rahaman Md Azharuddin Department of Computer Science and Engineering Aliah University Kolkata India

The wireless sensor networks' (WSNs') sensor nodes' (SNs') limited energy is a crucial factor to take into account since it can result in data loss or even the entire network failing. In order to address energy shortages or meet energy demands, wireless power transfer (WPT) was introduced as a means to overcome this problem. With WPT, SNs can have their battery power restored by recharging them through one or more chargers, thereby extending their lifespan. Planning a charging schedule for a mobile charger (MC) is an NP-hard issue. As part of our research, we present a priority-based charging scheduling algorithm that can be used on wireless rechargeable sensor networks (WRSNs). The suggested algorithm primarily considers the SNs' remaining energy and the timing of charging requests. To demonstrate the suggested algorithm's higher performance, we simulate it and compare the results with those of other commonly used approaches.

关键词： Wireless communication Wireless sensor networks Schedules scheduling algorithms Simulation Wireless power transfer Timing

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