采用离散粒子群算法的网格任务安全级调度

朱海; 王宇平; 权义宁; 王晓丽

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采用离散粒子群算法的网格任务安全级调度

更新时间：2025-07-09

- 采用离散粒子群算法的网格任务安全级调度
- Security Scheduling of Grid Tasks Based on the Discrete Particle Swarm Algorithm
- 西安交通大学学报 2010年44卷第6期页码：21-26
- 作者机构：
  
  西安电子科技大学计算机学院,西安,710071
- 作者简介：
- 基金信息：
  
  : 2009-09-18. 作者简介: 朱海(1978-),男,博士生;王宇平(联系人),男,教授,博士生导师. 基金项目: 国家自然科学基金资助项目(30873099)
- DOI：
  中图分类号： TP393
- 网络首发：2010-06-10，
  
  纸质出版：2010
- 稿件说明：
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朱海, 王宇平, 权义宁, 等. 采用离散粒子群算法的网格任务安全级调度[J]. 西安交通大学学报, 2010,44(6):21-26.

Security Scheduling of Grid Tasks Based on the Discrete Particle Swarm Algorithm[J]. 2010, 44(6): 21-26.
朱海, 王宇平, 权义宁, 等. 采用离散粒子群算法的网格任务安全级调度[J]. 西安交通大学学报, 2010,44(6):21-26. DOI：

Security Scheduling of Grid Tasks Based on the Discrete Particle Swarm Algorithm[J]. 2010, 44(6): 21-26. DOI：

摘要

针对异构网格环境中任务调度问题对所面临的安全性研究不足

在考虑了保密性、完整性和真实性等安全性因素的情况下

构造了相应的安全效益函数; 依据网格节点的历史行为特点

提出了节点的信誉度动态评估策略; 基于行为特点提出了一种离散粒子群算法

由此建立了任务安全级调度新模型.算法基于安全调度的离散空间特征给出了粒子的位置表示方法

从而克服了连续空间解决离散问题所造成的解空间冗余问题.采用分步计算和修改粒子位置的方式重新定义了粒子进化方程

避免了进化过程中速度之间的相互干扰问题.为了防止算法陷入局部最优

引入了均匀扰动速度.实验结果表明

与基于连续空间的粒子群算法和遗传算法相比

所提算法具有较快的收敛速度、较短的调度长度和较高的安全性能.

Abstract

For the lack of safety studies to the task scheduling under the heterogeneous grid environment

a security benefit function is constructed under the consideration of the performance requirements such as confidentiality

integrity

authenticity

and so on. A dynamic method to evaluate the credibility of nodes and a new discrete particle swarm optimization algorithm are proposed based on the characteristics of historical behavior of grid resource nodes. Then a new model to schedule task security levels is established. The algorithm gives representation for particle locations based on the discrete space features of security scheduling. Hence

solution space redundancy of scheduling based on continuous space is avoided. Particle evolution equation is redefined by means of stepwise calculation and modification of particle positions

which avoids the problem of mutual speed interference during the evolution. A uniform disturbance speed is introduced to prevent the algorithm into a local optimum. Experiments and comparisons with the particle swarm optimization algorithm based on continuous space and the genetic algorithm show that the proposed algorithm has a faster convergence speed

a shorter scheduling length

and a higher safety performance.

关键词

Keywords

references

CHAKRABARTI A, DAMODARAN A, SENGUPTA S.Grid computing security: a taxonomy [J]. IEEE Security & Privacy, 2008, 6(1): 44-51.

SONG S S, HWANG Kai, KWOK Yu Kwong. Risk-resilient heuristics and genetic algorithms for security-assured grid job scheduling [J]. IEEE Trans on Computers, 2006, 55(6): 703-719.

PARK J S, AN G, CHANDRA D. Trusted P2P computing environments with role-based access control [J]. Information Security, 2007, 1(3): 27-35.

袁禄来,曾国荪,姜黎立,等. 网格环境下基于信任模型的动态级调度[J]. 计算机学报,2006,29(7):1217-1224.

YUAN Lulai, ZENG Guosun, JIANG Lili, et al. Dynamic level scheduling based on trust model in grid computing [J]. Chinese Journal of Computers, 2006,29(7):1217-1224.

BRAUN T D, SLEGEL H J, BECJ N. A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems [J]. IEEE Trans on Parallel and Distributed Computing, 2001, 61(6):810-837.

薛正华,刘伟哲,董小社,等. 基于思维进化的集群作业调度方法研究 [J]. 西安交通大学学报,2008,42(6): 651-654.

XUE Zhenghua, LIU Weizhe, DONG Xiaoshe, et al. Research on mind evolutionary computation based job scheduling for server clusters[J]. Journal of Xi'an Jiaotong University, 2008,42(2): 651-654.

KENNEDY I, EBERHART R. Particle swarm optimization [C]∥Proceedings of the Fourth IEEE International Conference on Neural Networks. Piscataway, NJ, USA: IEEE Service Center, 1995:1942-1948.

倪庆剑,张志政,邢汉承. 一种基于可变多簇结构的动态概率粒子群优化算法[J].软件学报,2009,20(2): 339-349.

NI Qingjian, ZHANG Zhizheng, XING Hancheng. Dynamic probabilistic particle swarm optimization based on varying multi-cluster structure [J]. Journal of Software, 2009,20(2): 339-349.

王峰,邢科义,徐小平. 系统辨识的粒子群优化方法[J]. 西安交通大学学报,2009,43(2): 116-120.

WANG Feng, XING Keyi,XU Xiaoping. A system identification method using particle swarm optimization[J]. Journal of Xi'an Jiaotong University, 2009,43(2): 116-120.

季一木, 王汝传. 基于粒子群的网格任务调度算法研究[J].通信学报,2007, 28(10): 60-66.

JI Yimu, WANG Ruchuan. Study on PSO algorithm in solving grid task scheduling [J]. Journal on Communications, 2007, 28(10): 60-66.

XIE T, QIN X. Security-aware resource allocation for real-Time parallel jobs on homogenous and heterogeneous clusters [J]. IEEE Trans on Parallel and Distributed Systems, 2008, 19(5): 682-697.

ZHU H, WANG Y P. Evolutionary algorithm for solving constrained multi-objective grid tasks scheduling problem[C]∥Proceeding of the 2009 International Conference on Computer Network and Multimedia Technology. Washington, DC, USA: IEEE Computer Society, 2009:10-14.

ZHU H, WANG Y P. Security-driven task scheduling based on evolutionary algorithm[C]∥Proceedings of the 2008 Computational Intelligence and Security. Washington, DC, USA: IEEE Computer Society, 2008: 451-456.

孟宪福, 张晓燕. 对等网络环境下多目标约束的并行任务调度策略研究 [J]. 计算机集成制造系, 2008, 14(4): 761-766.

MENG Xianfu, ZHANG Xiaoyan. Parallel task scheduling strategy with multi-objective constrains in P2P [J].Computer Integrated Manufacturing Systems, 2008, 14(4): 761-766.

WU A S, YU H, JIN S, et al. An incremental genetic algorithm approach to multiprocessor scheduling [J]. IEEE Trans on Parallel and Distributed Systems, 2004, 15(9): 824-834.

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