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task scheduling algorithm based on value optimisation for anti-missile phased array radar

IET RADAR SONAR AND NAVIGATION 2019年第11期13卷 1883-1889页

作者： Yang, Shanchao Tian, Kangsheng Liu, Renzheng Air Force Early Warning Acad Early Warning Intelligence Dept Wuhan Hubei Peoples R China Rocket Force Command Coll Operat Lab Wuhan Hubei Peoples R China

A task scheduling algorithm based on value optimisation is proposed under comprehensive priority for anti-missile phased array radar. The model of threat degree is established for ballistic missile targets. The task comprehensive priority is obtained utilising a two-dimensional priority table which synthesises the target threat degree and the task deadline. Then, based on the comprehensive priority, each task gets a dynamic value function, instead of a fixed value as usual. In this way, the task value is enlarged when it is executed close to the desired execution time. A value optimisation model for task scheduling is constructed, and the genetic algorithm is utilised to solve this scheduling model. Thereby tasks can be executed as close as possible to the desired time, and the principle of scheduling timeliness can be better achieved. The performance of the proposed algorithm (PA) is compared with traditional scheduling algorithms by simulation experiments, as well as the impact that parameters of task value function have on scheduling performance is analysed. Simulation results show that compared to the traditional algorithms, the PA reduces the average time shift ratio and improves the value achieving ratio.

关键词： missiles phased array radar genetic algorithms scheduling optimisation task scheduling algorithm anti-missile array radar ballistic missile targets task comprehensive priority two-dimensional priority table target threat degree task deadline dynamic value function fixed value desired execution time value optimisation model genetic algorithm scheduling model scheduling timeliness traditional scheduling algorithms task value function scheduling performance traditional algorithms value achieving ratio

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task scheduling algorithm for Optical Grid architecture

Task scheduling algorithm for Optical Grid architecture

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Conference on Network Architectures, Management, and Applications IV, Pts 1 & 2

作者： Guo, Wei Sun, Zhenyu Wang, Zhengyu Zhang, Pengshan Ma, Jing Wang, Yan Jin, Yaohui Sun, Weiqiang Hu, Weisheng Shanghai Jiao Tong Univ State Key Lab Local Area Networks & Adv Opt Commu Shanghai 200240 Peoples R China

ISBN: (纸本)081946449X

Optical Grid that provides a way to integrate the geographical distributed resources for large-scale grid applications. This paper mainly focuses on the task scheduling issue in Optical Grid and proposes two task scheduling algorithms to minimize the total time or scheduling length required for a given task. A simulated optical grid has been addressed to demonstrate the effectiveness of the scheduling approach. The performance tests and analysis of the two algorithms are investigated to show the effect of the routing policy on the scheduling length. A more flexible policy is able to further improve scheduling length.

关键词： optical grid task scheduling algorithm communication contention

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task scheduling algorithm of Cyber-Physical System Base on Complex Industry and Big Data 12

Task Scheduling Algorithm of Cyber-Physical System Base on C...

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12th IEEE International Conference on Software Engineering and Service Science (IEEE ICSESS)

作者： Rong, Jiji Zhang, Tao Zhang, Lichen Guangdong Univ Technol Fac Comp Sci & Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781665415064

In order to address the problem of unbalanced load of cyber-physical systems caused by high data concurrency, heterogeneous resources, and complex task nature in complex industrial and big data environments, this paper proposes a dynamic feedback task scheduling algorithm based on queuing theory (Queuing Theory task scheduling). The algorithm firstly uses the cluster monitoring system to collect data on each server and waiting queue in the cluster. Then, the monitoring system calculates various performance indicators of the system based on the collected data to judge the status of the servers. Finally, the corresponding scheduling strategy will be executed. To verify the effectiveness of queuing theory task scheduling (QTTS), this paper uses SimEvents toolkit to build an experimental environment and conduct simulation experiments about the total time to complete the tasks and average waiting time of the tasks. The experimental results show that compared with the traditional scheduling algorithms RR and Min-Min, QTTS can effectively reduce the total time to complete the tasks and average waiting time of the tasks.

关键词： cyber-physical system task scheduling algorithm queuing theory dynamic feedback

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task scheduling algorithm Improvement in Cloud Computing

Task Scheduling Algorithm Improvement in Cloud Computing

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2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2024

作者： Goyal, Abhishek Vyas, Ritik Kumar Rathi, Kanak Singh, Ritesh Kiet Group of Institutions Dept. of Computer Science Ghaziabad India

ISBN: (纸本)9798350348460

Over the past few decades, academics have focused on task scheduling as one of the major issues in the cloud computing environment to enhance resource utilization and achieve cost-effective execution. In cloud computing, task scheduling is the process of allocating the most effective resources to do tasks while accounting for many factors, such as the task's execution time, user priority, cost, scalability, throughput, make-span, resource consumption, and so on. The primary objective of this paper is to give a comparative analysis of multiple Multiple-Criteria-decision-making (MCDM) algorithms in different cloud computing environments. This paper provides an analysis of algorithms like FCFS, AHP, & BWM to provide performance evaluation on various data sets. The results of the experiment demonstrate the advantages of the AHP algorithm, which outperforms other algorithms by getting the least waiting time. © 2024 IEEE.

关键词： Analytical Hierarchy Process (AHP) Best-Worst Method (BWM) Cloud Computing Multiple-Criteria-Decision-Making (MCDM) task scheduling algorithm

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Dynamic Measurement of task scheduling algorithm in Multi-Processor System

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Journal of Shanghai Jiaotong university(Science) 2019年第3期24卷 372-380页

作者： XIE Ying WU Jinzhao CHEN Jianying CUI Mengtian School of Computer Science and Technology Southwest Minzu UniversityChengdu 610041China Guangxi Key Laboratory of Hybrid Computational and IC Design Analysis Guangxi University for NationalitiesNanning 530006China Chengdu Institute of Computer Application Chinese Academy of SciencesChengdu 610041China University of Chinese Academy of Sciences Beijing 100049China

It is important to evaluate function behaviors and performance features of task scheduling algorithm in the multi-processor system.A novel dynamic measurement method(DMM)was proposed to measure the task scheduling algorithm’s correctness and *** a multi-processor system,task scheduling problem is represented by a combinatorial evaluation model,interactive Markov chain(IMC),and solution space of the algorithm with time and probability metrics is described by action-based continuous stochastic logic(aCSL).DMM derives a path by logging runtime scheduling actions and corresponding *** judging whether the derived path can be received by task scheduling IMC model,DMM analyses the correctness of *** judging whether the actual values satisfy label function of the initial state,DMM analyses the dependability of *** simulation shows that DMM can effectively characterize the function behaviors and performance features of task scheduling algorithm.

关键词： multi-processor task scheduling algorithm IMC aCSL dynamic measurement

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task scheduling algorithm for the communication, ocean, and meteorological satellite

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ETRI JOURNAL 2008年第1期30卷 1-12页

作者： Lee, Soojeon Jung, Won Chan Kim, Jae-Hoon ETRI Radio & Broadcasting Res Div Taejon South Korea

In this paper, we propose an efficient single-resource task scheduling algorithm for the Communication, Ocean, and Meteorological Satellite. Among general satellite planning functions such as constraint check, priority check, and task scheduling, this paper focuses on the task scheduling algorithm, which resolves conflict among tasks which have an exclusion relation and the same priority. The goal of the proposed task scheduling algorithm is to maximize the number of tasks that can be scheduled. The rationale of the algorithm is that a discarded task can be scheduled instead of a previously selected one depending on the expected benefit acquired by doing so. The evaluation results show that the proposed algorithm enhances the number of tasks that can be scheduled considerably.

关键词： task scheduling algorithm satellite mission planning system

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An Improved Binary PSO-based task scheduling algorithm in Green Cloud Computing 9

An Improved Binary PSO-based Task Scheduling Algorithm in Gr...

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9th International Conference on Communications and Networking in China (CHINACOM 2014)

作者： Xu, Lili Wang, Kun Ouyang, Zhiyou Qi, Xin Nanjing Univ Posts & Telecommun Key Lab Broadband Wireless Commun & Sensor Networ Nanjing 210003 Jiangsu Peoples R China

ISBN: (纸本)9781479959709

Cloud computing is experiencing a rapid development since a large amount of data need to be addressed. How to carry on the reasonable task scheduling plays a vital role in the efficiency of cloud computing. This paper proposes a green cloud task-scheduling algorithm (GCTA) based on the improved binary particle swarm optimization(BPSO). The main contribution of our work is avoiding matrix operations by using pipelined number for virtual machines and redefining the position and velocity of particle. Simulation shows that the proposed GCTA has less execution time, and reduces resource consumption accordingly.

关键词： task scheduling algorithm green cloud binary particle swarm optimization (BPSO)

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An Improved task scheduling algorithm Based on Multi-QoS in Cloud Computing

An Improved Task Scheduling Algorithm Based on Multi-QoS in ...

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International Conference on Mechanical, Electronic and Engineering Technology (ICMEET)

作者： Li, Fengsong Lou, Yuansheng Hohai Univ Coll Comp & Informat Nanjing 210000 Jiangsu Peoples R China

ISBN: (纸本)9783038350491

For the issues of quality of service (QoS) in the cloud computing raised by users, this paper proposes a strategy for QoS classification and builds tasks' priority function modeling and through priority scheduling tasks, assigning tasks to the reasonable resources, and finally to complete the task efficiently, improve the utilization of resources.

关键词： Cloud computing task scheduling algorithm QoS

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2PTS: A Two-Phase task scheduling algorithm for MapReduce

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2016年第9期E99D卷 2377-2380页

作者： Lim, Byungnam Shim, Yeeun Chung, Yon Dohn Korea Univ Dept Comp Sci & Engn Seoul South Korea

For an efficient processing of large data in a distributed system, Hadoop MapReduce performs task scheduling such that tasks are distributed with consideration of the data locality. The data locality, however, is limitedly exploited, since it is pursued one node at a time basis without considering the global optimality. In this paper, we propose a novel task scheduling algorithm that globally considers the data locality. Through experiments, we show our algorithm improves the performance of MapReduce in various situations.

关键词： MapReduce task scheduling algorithm data locality

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Optimization of artificial intelligence in localized big data real-time query processing task scheduling algorithm

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FRONTIERS IN PHYSICS 2024年 12卷

作者： Sun, Maojin Sun, Luyi CEICloud Data Storage Technol Beijing Co Ltd Beijing Peoples R China

Introduction The development of science and technology has driven rapid changes in the social environment, especially the rise of the big data environment, which has greatly increased the speed at which people obtain information. However, in the process of big data processing, the allocation of information resources is often unreasonable, leading to a decrease in efficiency. Therefore, optimizing task scheduling algorithms has become an urgent problem to be *** The study optimized task scheduling algorithms using artificial intelligence (AI) methods. A task scheduling algorithm optimization model was designed using support vector machine (SVM) and K-nearest neighbor (KNN) combined with fuzzy comprehensive evaluation. In this process, the performance differences of different nodes were considered to improve the rationality of resource *** and Discussion By comparing the task processing time before and after optimization with the total cost, the results showed that the optimized model significantly reduced task processing time and total cost. The maximum reduction in task processing time is 2935 milliseconds. In addition, the analysis of query time before and after optimization shows that the query time of the optimized model has also been reduced. The experimental results demonstrate that the proposed optimization model is practical in handling task scheduling problems and provides an effective solution for resource management in big data environments. This research not only improves the efficiency of task processing, but also provides new ideas for optimizing future scheduling algorithms.

关键词： task scheduling algorithm artificial intelligence (AI) support vector machines (SVM) big data optimization model

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