DPDS：processing resources scheduling algorithm

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (3): 128-132.

• 网络、通信与安全 • Previous Articles Next Articles

DPDS：processing resources scheduling algorithm

XIAO Gong-meng

Dept. of Automatization，Northwestern Polytechnical University，Xi’an 710072，China

Received:1900-01-01 Revised:1900-01-01 Online:2008-01-21 Published:2008-01-21
Contact: XIAO Gong-meng

DPDS：一种处理资源调度算法

肖共萌

西北工业大学自动化学院，西安 710072

通讯作者: 肖共萌

Abstract

Abstract: This paper proposes a novel processing resources scheduling algorithm oriented advanced Network Processors（NP），called Duplication-base Partial Dynamic Scheduling（DPDS）.It aims to improve the NP performance by combining the strategies of partial dynamic mapping and task duplication.DPDS differs from existing solutions in several aspects，e.g.，the processing elements are heterogeneous，fully-connected，and multi-threading，the application is decomposed into DAG tasks with continuous data-packets，and scheduling is conducted at both of initialization and run-time.Experimental results show the algorithm can increase the largest average throughput by about 30% than those without dynamic phase duplication

Key words: scheduling, Network Processors（NP）, task duplication, partial dynamic scheduling

摘要： 提出一种新颖的面向高级网络处理器（NP）的处理资源调度算法，称为基于复制的部分动态调度算法（Duplication-base Partial Dynamic Scheduling，DPDS），结合部分动态映射及任务复制策略，以改善NP的性能。DPDS从多个方面与已有算法不同，如处理单元是异构、全连通、多线程的，应用被分解为以持续数据包为输入的DAG任务，调度在初始化和运行时阶段均可调整。实验结果显示本算法比不具有动态复制阶段的算法在最大平均吞吐量上高出30％左右。

关键词: 调度, 网络处理器, 任务复制, 部分动态调度

XIAO Gong-meng. DPDS：processing resources scheduling algorithm[J]. Computer Engineering and Applications, 2008, 44(3): 128-132.

肖共萌. DPDS：一种处理资源调度算法[J]. 计算机工程与应用, 2008, 44(3): 128-132.

[1]	XIE Ruiqiang, ZHANG Huizhen. Two-Vector Wolf Pack Algorithm for Flexible Job Shop Scheduling Problem [J]. Computer Engineering and Applications, 2021, 57(7): 251-256.
[2]	WANG Yuncheng, ZHOU Chunhua, CHEN Chuxiang, WU Shanming, CHEN Bing. Extensible Intelligent Scheduling System Based on Two Fork Knowledge Tree Reasoning [J]. Computer Engineering and Applications, 2021, 57(5): 251-257.
[3]	ZHANG Chi, WANG Yuxin, FENG Zhen, GUO He. Energy-Efficient Task Scheduling Algorithm in Two-Layer Virtualized Cloud Architecture [J]. Computer Engineering and Applications, 2021, 57(3): 103-111.
[4]	LI Baoshuai, YE Chunming. Job Shop Scheduling Problem Based on Deep Reinforcement Learning [J]. Computer Engineering and Applications, 2021, 57(23): 248-254.
[5]	CAO Lijia, LIU Yang. Recent Advances in Scheduling Optimization of Automated Guided Vehicles in Manufacturing Workshops [J]. Computer Engineering and Applications, 2021, 57(21): 59-67.
[6]	TIAN Zhuojing, HUANG Zhenchun, ZHANG Yinong. Review of Task Scheduling Methods in Cloud Computing Environment [J]. Computer Engineering and Applications, 2021, 57(2): 1-11.
[7]	ZHOU Yamin, YANG Yongsheng, ZHONG Meisu, WANG Yusheng, XU Xueqian. Scheduling of Crossing Double ASC in Yard of Automated Terminals [J]. Computer Engineering and Applications, 2021, 57(2): 251-256.
[8]	SHI Yuqiang, TIAN Yongzheng, ZHANG Yuqi, SHI Xiaoqiu. Solving FJSP by Multi-population Genetic Algorithms with Complex Network Structure [J]. Computer Engineering and Applications, 2021, 57(2): 257-266.
[9]	ZHOU Yuanling, HU Xiaobing, JIANG Daiyu, LI Hang. Research on Optimization Algorithm of Workshop Scheduling Based on Improved NSGA-II [J]. Computer Engineering and Applications, 2021, 57(19): 274-281.
[10]	DAI Jiangtao, HAN Xiaolong. Coordinated Scheduling of Equipment in Container Terminals Considering Energy Consumption Under Different Job Status [J]. Computer Engineering and Applications, 2021, 57(19): 290-298.
[11]	LI Yuxin, LI Yueyue. Multi-objective Vehicle Scheduling Problem for JIT Procurement [J]. Computer Engineering and Applications, 2021, 57(12): 263-272.
[12]	GUO Jiali, WANG Qiuping, WANG Xiaofeng. Hybrid Moth Flame Algorithm with Learning Strategy and Neighboring Search [J]. Computer Engineering and Applications, 2021, 57(12): 170-179.
[13]	LIANG Chengji, HUANG Shuai. Scheduling Optimization of Multiple Container Blocks with Multiple Yard Cranes at Container Terminal Based on Time Window [J]. Computer Engineering and Applications, 2020, 56(8): 226-232.
[14]	YANG Yajie, CHANG Daofang, YU Fang. Multi-Resource Coordinated Scheduling of Automated Terminals Considering AGV Collision Avoidance [J]. Computer Engineering and Applications, 2020, 56(6): 246-253.
[15]	QIN Qin, LIANG Chengji. Optimization of Equipment Coordination Scheduling with Considering Buffer Space in Automated Container Terminal [J]. Computer Engineering and Applications, 2020, 56(6): 262-270.

DPDS：processing resources scheduling algorithm

DPDS：一种处理资源调度算法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics