Computer Science ›› 2015, Vol. 42 ›› Issue (6): 181-184.doi: 10.11896/j.issn.1002-137X.2015.06.039

Previous Articles     Next Articles

Linux System Dual Threshold Scheduling Algorithm Based on Characteristic Scale Equilibrium

CUI Yong-jun and ZHANG Yong-hua   

  • Online:2018-11-14 Published:2018-11-14

Abstract: In the design and application of embedded Linux operating system,operating system runs on different hardware platforms after transplantation,and it needs a task scheduling algorithm for effective implementation of process management and memory management to improve the operational efficiency of the system.Linux system dual threshold scheduling algorithm was proposed based on characteristic scale equilibrium.The kernel structure of embedded Linux was analyzed.The system task scheduling model was constructed.According to the various classifications of information such as task arrival rate,execution time,etc,the scale features are extracted.In the global task scheduling center,all the task data are integrated and input to the total system scheduler,and the scale optimization objective function is obtained.The feature scale balanced processing is taken.The characteristic time shaft is divided into the adjacent but not overlap task matching smoothing window,and the double threshold trade-off decision is used for task scheduling in Linux system.The simulation results show that the new algorithm has higher efficiency in Linux embedded task scheduling,utilization rate of CPU is better,and the overall performance is better than the traditional algorithm.

Key words: Characteristic scale,Linux operating system,Task scheduling,Equilibrium

[1] 张松慧,熊锦江.一种针对非平稳网络任务调度防冲突算法研究[J].科技通报,2013,9(10):143-145Zhang Song-hui,Xiong Jin-jiang.Non-Stationary Network Sche- duling Anti-Collision Algorithm Research [J].Bulletin of Science and Technology,2013,9(10):143-145
[2] Miorandi D,Sicari S,Pellegrini F D,et al.Internet of things:vision,applications and research challenges[J].Ad Hoc Networks,2012,10(7):1497-1516
[3] 李静梅,王雪,吴艳霞.一种改进的优先级列表任务调度算法[J].计算机科学,2014,1(5):20-23 Li Jing-mei,Wang Xue,Wu Yan-xia.Improved Priority List Task Scheduling Algorithm [J].Computer Science,2014,1(5):20-23
[4] Chong S K,Gaber M M,Krishnaswamy S,et al.Energy conservation in wireless sensor networks:a rule-based approach[J].Knowledge and Information Systems,2011,28(3):579-614
[5] 许丞,刘洪,谭良.Hadoop云平台的一种新的任务调度和监控机制[J].计算机科学,2013,0(1):112-117 Xu Cheng,Liu Hong,Tan Liang.New Mechanism of Monitoring on Hadoop Cloud Platform[J].Computer Science,2013,0(1):112-117
[6] 李仁发,刘彦,徐成.多处理器片上系统任务调度研究进展评述[J].计算机研究与发展,2008,45(9):1620-1629 Li Ren-fa,Liu Yan,Xu Cheng.A Survey of Task Scheduling Research Progress on Multiprocessor System-on-Chip [J].Computer Research and Development,2008,5(9):1620-1629
[7] 刘少伟,孔令梅,任开军,等.云环境下优化科学工作流执行性能的两阶段数据放置与任务调度策略[J].计算机学报,2011,4(11):2021-2130 Liu Shao-wei,Kong Ling-mei,Ren Kai-jun,et al.A Two-Step Data Placement and Task Scheduling Strategy for Optimizing Scientific Workflow Performance on Cloud Computing Platform [J].Chinese Journal of Computers,2011,4(11):2021-2130
[8] 孟宪福,解文利.基于免疫算法多目标约束P2P任务调度策略研究[J].电子学报,2011,39(1):101-107 Men Xian-fu,Xie Wen-li.Research on P2P Task Scheduling with Multi-objective Constraints Based on Immune Algorithm [J].Acta Electronica Sinica,2011,9(1):101-107
[9] 李文娟,张启飞,平玲娣,等.基于模糊聚类的云任务调度算法[J].通信学报,2012,3(3):146-154 Li Wen-juan,Zhang Qi-fei,Ping Ling-di,et al.Cloud Scheduling Algorithm Based on Fuzzy Clustering [J].Journal on Communications,2012,3(3):146-154
[10] 周浩,高远,朱昌平.基于双门限能量检测的选择式协作频谱感知[J].计算机仿真,2014,31(1):199-203 Zhou Hao,Gao Yuan,Zhu Chang-ping.Alternative Cooperative Spectrum Sensing Based on Double Threshold Energy Detection [J].Computer Simulation,2014,1(1):199-203
[11] 史少锋,刘宴兵.基于动态规划的云计算任务调度研究[J].重庆邮电大学:自然科学版,2012,24(6):687-692 Shi Shao-feng,Liu Yan-bing.Cloud Computing Task Scheduling Research Based on Dynamic Programming[J].Journal of Chongqing University of Posts and Telecommunications:Natural Science Edition,2012,24(6):687-692

No related articles found!
Full text



[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .