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Journal articles on the topic 'OS Scheduling Algorithm'

Author: Grafiati

Published: 4 June 2025

Last updated: 14 July 2025

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1

Mishra, Abhishek, and Pramod Kumar Mishra. "A Randomized Scheduling Algorithm for Multiprocessor Environments Using Local Search." Parallel Processing Letters 26, no. 01 (2016): 1650002. http://dx.doi.org/10.1142/s012962641650002x.

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The LOCAL(A, B) randomized task scheduling algorithm is proposed for fully connected multiprocessors. It combines two given task scheduling algorithms (A, and B) using local neighborhood search to give a hybrid of the two given algorithms. Objective is to show that such type of hybridization can give much better performance results in terms of parallel execution times. Two task scheduling algorithms are selected: DSC (Dominant Sequence Clustering as algorithm A), and CPPS (Cluster Pair Priority Scheduling as algorithm B) and a hybrid is created (the LOCAL(DSC, CPPS) or simply the LOCAL task sc

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Zouaoui, Sonia, Lotfi Boussaid, and Abdellatif Mtibaa. "Priority based round robin (PBRR) CPU scheduling algorithm." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 190–202. https://doi.org/10.11591/ijece.v9i1.pp190-202.

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This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algorithm canno

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Thirumala Rao, B., M. Susmitha, T. Swathi, and G. Akhil. "Implementation Of Hybrid Scheduler In Hadoop." International Journal of Engineering & Technology 7, no. 2.7 (2018): 868. http://dx.doi.org/10.14419/ijet.v7i2.7.11084.

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The paper focusses on priority based round robin scheduling algorithm for scheduling jobs in Hadoop environment. By Using this Proposed Scheduling Algorithm it reduces the starvation of jobs. And the advantage of priority scheduling is that the process with the highest priority will be executed first. Combining the both strategies of round robin and priority scheduling algorithm a optimized algorithm is to be implemented. Which works more efficiently even after considering all the parameters of scheduling algorithm. This proposed algorithm is also compared with existing round robin and priorit

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Zouaoui, Sonia, Lotfi Boussaid, and Abdellatif Mtibaa. "Priority based round robin (PBRR) CPU scheduling algorithm." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 190. http://dx.doi.org/10.11591/ijece.v9i1.pp190-202.

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<p>This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algori

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Huang, Xiaohui, Shuxia Zheng, Shilong Li, Jinxiang Wu, and Graham Spence. "Scheduling Problem of Biochemical Analyzer and Exploration of Neural Network-Greedy Algorithm." Journal of Medical Imaging and Health Informatics 10, no. 8 (2020): 1912–18. http://dx.doi.org/10.1166/jmihi.2020.3120.

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The mathematical model of biochemical analysis system was established based on neural network-greedy algorithm. The optimal task scheduling sequence was solved by neural network algorithm. At the same time, the local optimization was obtained by combining greedy algorithm. In this way, the task scheduling problem in biochemical analyzer was transformed into a mathematical problem, and the mathematical model of scheduling algorithm was established. On the platform of MATLAB, eight groups of simulation tests were carried out on the same task scheduling problem using the neural network-greedy sch

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Sreenath, M., and Dr P. A. Vijaya. "Boosted System Performance based on Execution Time Using LiMca Scheduling Algorithm." Journal of University of Shanghai for Science and Technology 23, no. 06 (2021): 1318–29. http://dx.doi.org/10.51201/jusst/21/06449.

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The scheduling algorithms have been examined by the process of task execution in a system to achieve maximum utilization of multiprocessors. Consequently, the research attempted to propose a new real-time scheduling algorithm to support a multiprocessor platform. The proposed scheduling algorithm, List Mcnaughton’s amalgamation (LiMca) scheduling algorithm has been developed for an optimum solution with the features of List and Mcnaughton’s scheduling algorithms to overcome the individual drawbacks (pre-emption and Precedence constraints). In LiMca, Workload has been distributed to the process

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Liu, Yu Jie. "Modeling and Analysis for Optimization Mode of City Bus Operator Scheduling Management." Applied Mechanics and Materials 513-517 (February 2014): 3220–23. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3220.

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This paper proposes a bus route scheduling management model based on Ant Colony Optimization and traditional scheduling model. It optimizes the existing bus route scheduling management model according to Ant Colony algorithm, enhances the performance of both Ant Colony algorithm and the traditional scheduling model, and improves the optimal performance of the combining algorithm. The experiment results show that, the proposed algorithm can effectively deal with the bus route scheduling management, and the optimization result obtained is obviously better than the traditional algorithms. Further

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Wang, Guan, Yuxin Wang, Hui Liu, and He Guo. "HSIP: A Novel Task Scheduling Algorithm for Heterogeneous Computing." Scientific Programming 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3676149.

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High-performance heterogeneous computing systems are achieved by the use of efficient application scheduling algorithms. However, most of the current algorithms have low efficiency in scheduling. Aiming at solving this problem, we propose a novel task scheduling algorithm for heterogeneous computing named HSIP (heterogeneous scheduling algorithm with improved task priority) whose functionality relies on three pillars: (1) an improved task priority strategy based on standard deviation with improved magnitude as computation weight and communication cost weight to make scheduling priority more re

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Ni, Qiufen, Chuanhe Huang, Panos M. Pardalos, Jia Ye, and Bin Fu. "Different Approximation Algorithms for Channel Scheduling in Wireless Networks." Mobile Information Systems 2020 (November 16, 2020): 1–13. http://dx.doi.org/10.1155/2020/8836517.

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We introduce a new two-side approximation method for the channel scheduling problem, which controls the accuracy of approximation in two sides by a pair of parameters f , g . We present a series of simple and practical-for-implementation greedy algorithms which give constant factor approximation in both sides. First, we propose four approximation algorithms for the weighted channel allocation problem: 1. a greedy algorithm for the multichannel with fixed interference radius scheduling problem is proposed and an one side O 1 -IS-approximation is obtained; 2. a greedy O 1 , O 1 -approximation al

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Xue, Sheng Jun, and Fang Fang Liu. "Application of an Improved Immune Evolutionary Algorithm to Grid Task Scheduling." Advanced Materials Research 219-220 (March 2011): 1383–88. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.1383.

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Grid task scheduling is an NP problem , performance of scheduling algorithms greatly influences scheduling results. Aiming at the shortages of the existing Evolutionary Algorithm, such as premature convergence, search process easily falling into local optimum, poor scheduling results and so on, this paper proposed an improved immune Evolutionary Algorithm which introduced concentration mechanism in the immune system into Immune Evolutionary Algorithm and adjusted regulator to adaptive function. Simulation experiment shows that, convergence speed and performance of the improved algorithm are si

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11

Li, Yudong, Jinquan Ma, Zongfu Xie, Zeming Hu, Xiaolong Shen, and Kun Zhang. "A Scheduling Method for Heterogeneous Signal Processing Platforms Based on Quantum Genetic Algorithm." Applied Sciences 13, no. 7 (2023): 4428. http://dx.doi.org/10.3390/app13074428.

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Currently, many problems such as variable signal resources, complex execution environments, and low efficiency of scheduling algorithms are faced by heterogeneous signal processing platforms. The task scheduling algorithm is one of the key factors that directly affect the performance of the processing platform. In order to solve the problems of low efficiency of task scheduling algorithms and high computational cost of processors, a heterogeneous platform scheduling algorithm based on the quantum genetic algorithm is proposed in this paper. The algorithm constructs a task scheduling model by u

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12

Finkelstein, L., S. Markovitch, and E. Rivlin. "Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources." Journal of Artificial Intelligence Research 19 (August 1, 2003): 73–138. http://dx.doi.org/10.1613/jair.1195.

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The performance of anytime algorithms can be improved by simultaneously solving several instances of algorithm-problem pairs. These pairs may include different instances of a problem (such as starting from a different initial state), different algorithms (if several alternatives exist), or several runs of the same algorithm (for non-deterministic algorithms). In this paper we present a methodology for designing an optimal scheduling policy based on the statistical characteristics of the algorithms involved. We formally analyze the case where the processes share resources (a single-processor mo

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Wu, Lin, Yu Jing Wang, and Chao Kun Yan. "Performance Comparison of Energy-Aware Task Scheduling with GA and CRO Algorithms in Cloud Environment." Applied Mechanics and Materials 596 (July 2014): 204–8. http://dx.doi.org/10.4028/www.scientific.net/amm.596.204.

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With energy problem of cloud data center is becoming more and more serious, the BoT scheduling algorithm only considering the timespan is not applicable to the cloud computing environment. In order to explore the energy-aware task scheduling algorithm performance, this paper validates simulation experiments with GA algorithms and CRO algorithms, to optimize the makespan as the main objective, to optimize energy consumption indicators for the secondary objective. Experiments show that, GA algorithms and CRO algorithm can be applied to different scenarios, while optimizing makespan, but also to

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Cui, Qing Quan, Ya Hui Wang, Dong Wei, and Shao Jun Zhang. "Research on the Switch Scheduling Algorithm of Networked Control System." Advanced Materials Research 433-440 (January 2012): 3553–59. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3553.

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Networked Control System is the focus of current research in control field, and the use of a shared network introduces new challenges, therefore, it is significant to research scheduling algorithms for improving the control and schedule performance of NCS. In the paper, according to the challenges existing in scheduling algorithms, a new scheduling algorithm called Switch scheduling is proposed, and the calculation method of switching conditions is also given. In the proposed algorithm, network-induced delay and network utilization are considered to satisfy the different network condition with

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15

Sangeetha, Marikkannan, Leelavathi, Kalaiselvi Udhayasuriyan, and Kavitha. "Scheduling and Allocation Algorithm for an Elliptic Filter." International Journal of Advanced Information Technology (IJAIT) 2, no. 2 (2012): 93–101. https://doi.org/10.5281/zenodo.3550561.

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A new evolutionary algorithm for scheduling and allocation algorithm is developed for an elliptic filter. The elliptic filter is scheduled and allocated in the proposed work which is then compared with the different scheduling algorithms like As Soon As Possible algorithm, As Late As Possible algorithm, Mobility Based Shift algorithm, FDLS, FDS and MOGS. In this paper execution time and resource utilization is calculated using different scheduling algorithm for an Elliptic Filter and reported that proposed Scheduling and Allocation increases the speed of operation by reducing the control step.

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Panchal, Sonia, and Satinder Pal. "An Effective Approach to Contention Based Bandwidth Request Mechanism in WiMAX Networks." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 1 (2012): 106–12. http://dx.doi.org/10.24297/ijct.v3i1b.2749.

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In this paper the IEEE 802.16 standard based Mobile WiMAX (Worldwide Interoperability for Microwave Access) system is investigated for the purpose of Quality of Service provisioning. As a potential solution, scheduling algorithms have been taken into major concern. Within the pool of scheduling algorithms and for the purpose Contention based bandwidth request resolution, the Modified Contention Based BW Resolution algorithm (MCB-BWR-Scheme) is proposed. Supported by the fact that the standard does not emphasize a specific scheduling algorithm for contention period based services, therefore, th

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17

Rezaei, Farshad, and Shamsollah Ghanbari. "TRUST BASE JOB SCHEDULING IN CLOUD COMPUTING." Azerbaijan Journal of High Performance Computing 4, no. 1 (2021): 39–47. http://dx.doi.org/10.32010/26166127.2021.4.1.39.47.

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Cloud computing is a new technology recently being developed seriously. Scheduling is an essential issue in the area of cloud computing. There is an extensive literature concerning scheduling in the area of distributed systems. Some of them are applicable for cloud computing. Traditional scheduling methods are unable to provide scheduling in cloud environments. According to a simple classification, scheduling algorithms in the cloud environment are divided into two main groups: batch mode and online heuristics scheduling. This paper focuses on the trust of cloud-based scheduling algorithms. Ac

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Chen, Yumeng, Songlin Liu, Zongmiao He, and Xiang Ling. "A Tetris-Based Task Allocation Strategy for Real-Time Operating Systems." Electronics 14, no. 1 (2024): 98. https://doi.org/10.3390/electronics14010098.

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Real-time constrained multiprocessor systems have been widely applied across various domains. In this paper, we focus on the scheduling algorithm for directed acyclic graph (DAG) tasks under partitioned scheduling on multiprocessor systems. Effective real-time task scheduling algorithms significantly enhance the performance and stability of multiprocessor systems. Traditional real-time task scheduling algorithms commonly rely on a single-heuristic parameter as the reference for task allocation, which typically results in suboptimal performance. Inspired by the Tetris algorithm, we propose a no

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Sun, Lei, Weimin Shi, Chang Xuan, and Yongchao Zhang. "Research on Scheduling Algorithm of Knitting Production Workshop Based on Deep Reinforcement Learning." Machines 12, no. 8 (2024): 579. http://dx.doi.org/10.3390/machines12080579.

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Intelligent scheduling of knitting workshops is the key to realizing knitting intelligent manufacturing. In view of the uncertainty of the workshop environment, it is difficult for existing scheduling algorithms to flexibly adjust scheduling strategies. This paper proposes a scheduling algorithm architecture based on deep reinforcement learning (DRL). First, the scheduling problem of knitting intelligent workshops is represented by a disjunctive graph, and a mathematical model is established. Then, a multi-proximal strategy (multi-PPO) optimization training algorithm is designed to obtain the

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20

Wu, Wei, Jun Sun, and Tong Hui Wu. "A Semi-Persistent Scheduling Algorithm for VoIP in LTE-Advanced System." Advanced Materials Research 1046 (October 2014): 343–47. http://dx.doi.org/10.4028/www.scientific.net/amr.1046.343.

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The scheduling algorithm is one of the key technologies in LTE-Advanced system. In this paper, a semi-persistent scheduling algorithm designed for the VoIP service in LTE-Advanced system is proposed. The time-frequency resource will be allocated to the users according to the semi-persistent scheduling algorithm based on the gain for each user on the certain RB. By introducing the mechanism and procedure, analyzing the proposed semi-persistent scheduling algorithm combined the source coding (SC) or modulation and coding scheme (MCS) techniques, the superiority of the proposed algorithm is shown

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Zhan, Xiaojuan, Zhiqiang Xie, and Dengju Yao. "An Integrated Scheduling Algorithm Based on a Process End Time-Driven and Long-Time Scheduling Strategy." Symmetry 14, no. 10 (2022): 2106. http://dx.doi.org/10.3390/sym14102106.

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The integrated scheduling problem is a classical combinatorial optimization problem. The existing integrated scheduling algorithms generally adopt the short-time scheduling strategy that does not fully consider the impact of the degree of process parallelism on scheduling results. In order to further optimize the total processing time of a product and the utilization rate of a device, an integrated scheduling algorithm based on a process end time-driven and the long-time scheduling strategy is proposed. The proposed integrated scheduling algorithm sets up a separate candidate process queue for

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Ghaffar, Akbari &. Yousufzai. "Milad Scheduling Algorithm (MSA)." Kardan Journal of Engineering and Technology 3, no. 1 (2021): 110–16. https://doi.org/10.31841/KJET.2022.22.

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In today's world, a lot of software is operational in different fields. One of the most important types of software is the operating system. It is an immense set of system software in terms of its functionality and size. It directly interacts with the hardware, fully controls different hardware, and provides a bridge between the user and the hardware. One of the important tasks of the operating system is to schedule the processes so that they can be completed at an acceptable time. Different scheduling algorithms have been proposed, like First Come, First Served (FCFS), Shortest Job First

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N. Sirhan, Najem, and Manel Martinez-Ramon. "Cognitive Radio Resource Scheduling using Multi-Agent Q-Learning for LTE." International journal of Computer Networks & Communications 14, no. 02 (2022): 77–95. http://dx.doi.org/10.5121/ijcnc.2022.14205.

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In this paper, we propose, implement, and test two novel downlink LTE scheduling algorithms. The implementation and testing of these algorithms were in Matlab, and they are based on the use of Reinforcement Learning (RL), more specifically, the Q-learning technique for scheduling two types of users. The first algorithm is called a Collaborative scheduling algorithm, and the second algorithm is called a Competitive scheduling algorithm. The first type of the scheduled users is the Primary Users (PUs), and they are the licensed subscribers that pay for their service. The second type of the sched

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Elhafiz, Afaf Abd Elkader Abd. "HASA: Half The Average Scheduling Algorithm." Circulation in Computer Science 2, no. 9 (2017): 35–39. http://dx.doi.org/10.22632/ccs-2017-252-58.

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The process of assigning independent tasks to resources with the aim of optimizing some objective functions is known as scheduling. The efficient scheduling of independent tasks to improve the performance of a system is an important problem. Several algorithms are developed to schedule tasks on their resources to minimize the makespan. One of these algorithms is ACTA (Average of Completion Times Algorithm). This paper proposes an algorithm HASA (Half the Average Scheduling Algorithm) that ameliorates the makespan produced by ACTA. Experimental results show that the proposed algorithm gives mak

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Yanwari, Muhammad Irwan, Anton Satria Prabuwono, Tri Raharjo Yudantoro, Nurseno Bayu Aji, Wiktasari, and Slamet Handoko. "Priority Scheduling Implementation for Exam Schedule." Indonesian Journal of Information Systems 5, no. 2 (2023): 80–89. http://dx.doi.org/10.24002/ijis.v5i2.6871.

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Scheduling is a common problem that has been raised for a long time. Many algorithms have been created for this problem. Some algorithms offer flexibility in terms of constraints and complex operations. Because of that complexity, many algorithms will need huge computation resources and execution time. A platform like a web application has many restrictions such as execution time and computation resources. A complex algorithm is not suited for the web application platform. Priority scheduling is a scheduling algorithm based on a priority queue. Every schedule slot will produce a queue based on

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Izadkhah, Habib. "Learning Based Genetic Algorithm for Task Graph Scheduling." Applied Computational Intelligence and Soft Computing 2019 (February 3, 2019): 1–15. http://dx.doi.org/10.1155/2019/6543957.

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Nowadays, parallel and distributed based environments are used extensively; hence, for using these environments effectively, scheduling techniques are employed. The scheduling algorithm aims to minimize the makespan (i.e., completion time) of a parallel program. Due to the NP-hardness of the scheduling problem, in the literature, several genetic algorithms have been proposed to solve this problem, which are effective but are not efficient enough. An effective scheduling algorithm attempts to minimize the makespan and an efficient algorithm, in addition to that, tries to reduce the complexity o

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Zhang, Qingnian, Ying Gao, Zhao Chen, and Xiuxia Zhang. "Scheduling Optimization Algorithm Based on Hadoop." Journal of Advances in Computer Networks 3, no. 3 (2015): 197–200. http://dx.doi.org/10.7763/jacn.2015.v3.166.

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K, Kousalya, and Balasubramanie P. "Online Grid Scheduling Using Ant Algorithm." International Journal of Engineering and Technology 1, no. 1 (2009): 21–26. http://dx.doi.org/10.7763/ijet.2009.v1.4.

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Huang, Ying Jie, Xi Fan Yao, Dong Yuan Ge, and Yong Xiang Li. "Entropy-Enhanced Genetic Algorithm with Tabu Search for Job Shop Scheduling Problems." Advanced Materials Research 590 (November 2012): 557–62. http://dx.doi.org/10.4028/www.scientific.net/amr.590.557.

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By combining Genetic algorithm with Tabu search algorithm and adjusting crossover rate and mutation rate based on information entropy, a hybrid genetic algorithm was proposed for larger-scale job shop scheduling problems, and the benchmark instances were used to verify the algorithm with simulation. Simulation results show that the proposed algorithm can solve larger-scale job shop scheduling problems, and it has obvious advantages over traditional scheduling algorithms.

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Lu, You Wei, Zhen Zhen Xu, and Feng Xia. "Prediction-Based Independent Task Scheduling for Heterogeneous Distributed Computing Systems." Advanced Materials Research 457-458 (January 2012): 1039–46. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.1039.

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Independent task scheduling algorithms in distributed computing systems deal with three main conflicting factors including load balance, task execution time and scheduling cost. In this paper, the problem of scheduling tasks arriving at a low rate and with long execution time in heterogeneous computing systems is studied, and a new scheduling algorithm based on prediction is proposed. This algorithm evaluates the utility of task scheduling based on statistics and prediction to solve the influence of heterogeneous computing systems. The experimental results reveal that the proposed algorithm ad

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Zhang, Yan-Qing, and Abraham Kandel. "Fuzzy CPU Scheduling." International Journal on Artificial Intelligence Tools 06, no. 02 (1997): 211–25. http://dx.doi.org/10.1142/s0218213097000128.

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In this paper, the methodology of using fuzzy logic techniques to improve the performance of CPU scheduling is concisely proposed. To make CPU work efficiently in the multiple-factor environment, we developed a fuzzy CPU scheduling algorithm to deal with the fuzziness of CPU scheduling. The simulations of different CPU scheduling algorithms have shown that the fuzzy CPU scheduling algorithm is an efficient scheme for compromising multiple factors.

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Lv, Shen-min. "An Annealing Memetic Algorithm for Instructional Scheduling." International Journal of Emerging Technologies in Learning (iJET) 13, no. 11 (2018): 17. http://dx.doi.org/10.3991/ijet.v13i11.9601.

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In order to solve the problems of large-scale instructional scheduling, many constraints, and complex interrelation, it is studied based on the changes in the scheduling problem and the adjustment of related algorithms. Firstly, the problem of instructional scheduling is described as a whole, and the relationship between each stage, in particular the impact of the combined plan on scheduling is also described, and an optimization plan is proposed. Then the optimal scheduling scheme is solved with Memetic algorithm. According to the constraints, the fitness value function in the algorithm is de

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Shi, Heng Hua, Xin Xu, Yu Jie Wang, and Yuan Yue Yang. "Research on Queue Scheduling Algorithm Modeling and Analysis." Advanced Materials Research 542-543 (June 2012): 1390–93. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.1390.

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With the development of network technology and the wide use of the Internet, QoS has attracted wide attention. Queue scheduling algorithm of Router is an important core technology of the network resource management for QoS. Through controlling usage of the link bandwidth of the different type groups, the different traffics have the different levels of service. Based on the analysis and modeling of FIFO, PQ, and WFQ scheduling algorithms, the simulation experiment simulate three different priority video conferencing traffic, and apply FIFO, PQ, and WFQ scheduling algorithms on the bottleneck li

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Sasmita, Kumari Nayak. "Nature inspired algorithms in dynamic task scheduling: A review." World Journal of Advanced Research and Reviews 20, no. 3 (2023): 829–33. https://doi.org/10.5281/zenodo.12748311.

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The process of scheduling involves allocating shared resources gradually so that tasks can be completed effectively within the allotted time. In task scheduling and resource allocation, the terms are used independently for tasks and resources, respectively. In computer science and operational management, scheduling is a hot topic. Efficient schedules guarantee system effectiveness, facilitate sound decision-making, reduce resource waste and expenses, and augment total productivity. Selecting the most accurate resources to complete work items and schedules for computing and business process exe

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Li, Xiao Fang. "Simulation on Task Scheduling for Multiprocessors Based on Improved Neural Network." Applied Mechanics and Materials 513-517 (February 2014): 2293–96. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.2293.

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This paper mainly discusses task scheduling for multiprocessors. Application requires higher performance of the multiprocessors task scheduling systems. The traditional algorithms majorly consider the accuracy and neglect the real-time performance. In order to improve the real-time performance while maintaining the accuracy, the paper proposes a task scheduling algorithm (GA-ACO) for multiprocessors based on improved neural network. It first builds mathematical models for task scheduling of multiprocessor systems, and then introduces genetic algorithms to quickly find feasible solutions. The s

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Liu, Daqian, Zhewei Zhang, Yuntao Shi, Yingying Wang, Jingcheng Guo, and Zhenwu Lei. "Start Time Planning for Cyclic Queuing and Forwarding in Time-Sensitive Networks." Mathematics 12, no. 21 (2024): 3382. http://dx.doi.org/10.3390/math12213382.

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Time-sensitive networking (TSN) is a kind of network communication technology applied in fields such as industrial internet and intelligent transportation, capable of meeting the application requirements for precise time synchronization and low-latency deterministic forwarding. In TSN, cyclic queuing and forwarding (CQF) is a traffic shaping mechanism that has been extensively discussed in the recent literature, which allows the delay of time-triggered (TT) flow to be definite and easily calculable. In this paper, two algorithms are designed to tackle the start time planning issue with the CQF

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Fu, Weiyu, and Lixia Wang. "Load Balancing Algorithms for Hadoop Cluster in Unbalanced Environment." Computational Intelligence and Neuroscience 2022 (October 7, 2022): 1–9. http://dx.doi.org/10.1155/2022/1545024.

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Considering that in the process of job scheduling, the cluster load should be prebalanced rather than remedied when the load is seriously unbalanced; therefore, in this paper, the task scheduling flow of the Hadoop cluster is analyzed deeply. On the Hadoop platform, a self-dividing algorithm is proposed for load balancing. An intelligent optimization algorithm is used to solve load balance. A dynamic feedback load balancing scheduling method is proposed from the point of view of task scheduling. In order to solve the shortcoming of the fair scheduling algorithm, this paper proposes two ways to

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Huang, Xiabao, Zailin Guan, and Lixi Yang. "An effective hybrid algorithm for multi-objective flexible job-shop scheduling problem." Advances in Mechanical Engineering 10, no. 9 (2018): 168781401880144. http://dx.doi.org/10.1177/1687814018801442.

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Genetic algorithm is one of primary algorithms extensively used to address the multi-objective flexible job-shop scheduling problem. However, genetic algorithm converges at a relatively slow speed. By hybridizing genetic algorithm with particle swarm optimization, this article proposes a teaching-and-learning-based hybrid genetic-particle swarm optimization algorithm to address multi-objective flexible job-shop scheduling problem. The proposed algorithm comprises three modules: genetic algorithm, bi-memory learning, and particle swarm optimization. A learning mechanism is incorporated into gen

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Qiu, Jian Lin, Li Chen, Jian Ping Chen, Xiang Gu, and Yan Yun Chen. "Grid-Based Task Scheduling PMTS Algorithm." Applied Mechanics and Materials 121-126 (October 2011): 4491–97. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.4491.

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This paper analyses the Min-min algorithm and its improved algorithms through the performances of load balance, time span, quality of service and economic principle. Based on the analysis of the merits of these algorithms, we propose an improved algorithm as PMTS (Priority-based maximum time-span algorithm) by integrating. In the instance of the application, we analyse and compare the performances of these algorithms, and experimental results show that, PMTS algorithm is better than other algorithms in the comprehensive performance of load-balance, time-span, quality of service and other aspec

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Sneha, Sneha, and Shoney Sebastian. "Improved fair Scheduling Algorithm for Hadoop Clustering." Oriental journal of computer science and technology 10, no. 1 (2017): 194–200. http://dx.doi.org/10.13005/ojcst/10.01.26.

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Traditional way of storing such a huge amount of data is not convenient because processing those data in the later stages is very tedious job. So nowadays, Hadoop is used to store and process large amount of data. When we look at the statistics of data generated in the recent years it is very high in the last 2 years. Hadoop is a good framework to store and process data efficiently. It works like parallel processing and there is no failure or data loss as such due to fault tolerance. Job scheduling is an important process in Hadoop Map Reduce. Hadoop comes with three types of schedulers namely

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Sreenath, M., and P. A. Vijaya. "Enhancement of system performance using PeSche scheduling algorithm on multiprocessors." i-manager's Journal on Power Systems Engineering 11, no. 3 (2023): 37. http://dx.doi.org/10.26634/jps.11.3.20277.

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The scheduling techniques have been investigated by the job execution process in a system to maximize multiprocessor utilization. Dynamic Power Management (DPM) and Dynamic Voltage and Frequency Scaling (DVFS) represent two general strategies for lowering energy use. Performance enhanced Scheduling (PeSche) is a proposed scheduling algorithm designed for an optimal solution. CodeBlocks were utilized to run extensive simulations. In terms of computing performance (average waiting time and average turnaround time), the PeSche scheduling algorithm outperformed recently reported scheduling algorit

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Singh, Lalla, and Neha Agarwal. "An Improved Min-Min Task Scheduling Algorithm with Grid Utilization and Minimized Makespan." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 14, no. 8 (2015): 5960–66. http://dx.doi.org/10.24297/ijct.v14i8.1860.

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Grid computing is hardware and software infrastructure which offers a economical, distributable, coordinated and credible access to strong computational abilities [1]. For optimal use of the abilities of large distributed systems, necessitate for successful and proficient scheduling algorithms is enforced. For diminution of total completion time and improvement of load balancing, many algorithms have been executed. In this paper, our goal is to propose new scheduling algorithm based on well known task scheduling algorithm i.e. Min-Min[1]. The proposed algorithm tries to use the advantages of t

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Putra, Tri Dharma, and Rakhmat Purnomo. "Simulation of Priority Round Robin Scheduling Algorithm." Sinkron 7, no. 4 (2022): 2170–81. http://dx.doi.org/10.33395/sinkron.v7i4.11665.

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In this journal, simulation of priority round robin scheduling algorithm is presented. To imitate the processes of operating system operation, simulation can be used. By simulation, model is used, namely models that represent the characteristics or behaviour of systems. Process scheduling is one important operation in operating system. OS-SIM can be used to model and simulate the operations of process scheduling. Some scheduling algorithms are available in modern operating systems, like First come First Serve (FCFS), Shortest Job First (SJF), Round Robin (RR), Priority Scheduling or combinatio

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Yuniartha, Deny Ratna, Nur Mayke E. Normasari, Joko Waluyo, Nur Aini Masruroh, and Muhammad Kusumawan Herliansyah. "Techniques for Improving Genetic Algorithms in Solving Operating Room Scheduling Problems: An Integrative Review." International Journal of Industrial Engineering and Engineering Management 6, no. 1 (2024): 35–46. http://dx.doi.org/10.24002/ijieem.v6i1.8903.

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Operating room scheduling is a complex process that involves various resources and takes the interests of many parties into consideration. The genetic algorithm is the frequently used metaheuristic algorithm to solve a large-size operating room scheduling problem. Many techniques have been developed to improve the genetic algorithms' performance in dealing with the operating room scheduling complexity. In this paper, we survey available literature to identify improvement techniques used at each stage of the genetic algorithm and capture the underlying problems. This review provides a mapping o

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Wang, Jun, and Ji Ying Ma. "A Delay Optimization of Non-Periodic Information for the Scheduling Algorithm." Advanced Materials Research 216 (March 2011): 364–67. http://dx.doi.org/10.4028/www.scientific.net/amr.216.364.

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The optimal scheduling algorithm based on non-periodic information is model and analyzed. Compared with typical scheduling algorithms, it improves non-periodic tasks theoretical delay. Finally, the simulation shows that the scheduling algorithm is effective in reducing delay problems of the non-periodic communication task.

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Chen, Peng, Yunni Xia, and Chun Yu. "A Novel Reinforcement-Learning-Based Approach to Workflow Scheduling Upon Infrastructure-as-a-Service Clouds." International Journal of Web Services Research 18, no. 1 (2021): 21–33. http://dx.doi.org/10.4018/ijwsr.2021010102.

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Recently, the cloud computing paradigm has become increasingly popular in large-scale and complex workflow applications. The workflow scheduling problem, which refers to finding the most suitable resource for each task of the workflow to meet user defined quality of service, attracts considerable research attention. Multi-objective optimization algorithms in workflow scheduling have many limitations (e.g., the encoding schemes in most existing heuristic-based scheduling algorithms require prior experts' knowledge), and thus, they can be ineffective when scheduling workflows upon dynamic cloud

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Shanthini, J., T. Kalaikumaran, and S. Karthik. "Hybrid Scheduling Model for Independent Grid Tasks." Scientific World Journal 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/692084.

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Grid computing facilitates the resource sharing through the administrative domains which are geographically distributed. Scheduling in a distributed heterogeneous environment is intrinsically very hard because of the heterogeneous nature of resource collection. Makespan and tardiness are two different measures of scheduling, and many of the previous researches concentrated much on reduction of makespan, which measures the machine utilization. In this paper, we propose a hybrid scheduling algorithm for scheduling independent grid tasks with the objective of reducing total weighted tardiness of

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Loo, Chang Herng, M. Zulfahmi Toh, Ahmad Fakhri Ab. Nasir, Nur Shazwani Kamaruddin, and Nur Hafieza Ismail. "Efficiency and Accuracy of Scheduling Algorithms for Final Year Project Evaluation Management System." MEKATRONIKA 5, no. 2 (2023): 23–31. http://dx.doi.org/10.15282/mekatronika.v5i2.9973.

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Scheduling algorithms play a crucial role in optimizing the efficiency and precision of scheduling tasks, finding applications across various domains to enhance work productivity, reduce costs, and save time. This research paper conducts a comparative analysis of three algorithms: genetic algorithm, hill climbing algorithm, and particle swarm optimization algorithm, with a focus on evaluating their performance in scheduling presentations. The primary goal of this study is to assess the effectiveness of these algorithms and identify the most efficient one for handling presentation scheduling ta

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Jin, Xin. "Application of Metaheuristic algorithm in intelligent logistics scheduling and environmental sustainability." Intelligent Decision Technologies 18, no. 3 (2024): 1727–40. http://dx.doi.org/10.3233/idt-240280.

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In response to the problems of low efficiency, high cost, and serious environmental pollution faced by traditional logistics scheduling methods, this article introduced the Metaheuristic algorithm into intelligent logistics scheduling and environmentally sustainable development. This article took the Metaheuristic algorithm as the research object. It was based on an in-depth analysis of its core ideas and unique advantages, combined intelligent logistics scheduling with relevant theories and methods such as green environmental protection, and innovatively constructed an intelligent logistics s

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Bassim M. Salih, Omer K. Jasim Mohammad,. "Improving Task Scheduling in Cloud Datacenters by Implementation of an Intelligent Scheduling Algorithm." Journal of Electrical Systems 20, no. 3s (2024): 1465–78. http://dx.doi.org/10.52783/jes.1522.

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The need for mobile and online Apps and services has led to rapid growth in cloud computing services. The rapid increase in growth highlights the importance of reducing the time required for scheduling and efficiently utilizing resources in a dynamic setting. Consequently, numerous scheduling algorithms have been devised to address these problems by employing intelligent scheduling approaches, including Genetic Algorithms, greedy algorithm, Antlion Optimizer, Ant Colony optimization, and Cuckoo Intelligent Algorithm. This study provides an overview of intelligent optimization strategies, with

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