A trust model-based task scheduling algorithm for data-intensive application

被引：2

作者：

Xu Y. ^{[1
]}

Qu W. ^{[1
]}

机构：

[1] College of Information Science and Technology, Dalian Maritime University, Dalian

来源：

Proceedings - 2011 6th Annual ChinaGrid Conference, ChinaGrid 2011 | 2011年

关键词：

data-intensive; Min-Min; task scheduling; trust;

D O I：

10.1109/ChinaGrid.2011.16

中图分类号：

学科分类号：

摘要：

With the increase of data-intensive application, the amount of data that the task requires becomes much larger and the task scheduling performance is greatly affected by the data transfer overhead. In grid, establishing trust model is considered to be an important measure of improving the grid security. Therefore, considering the two problems above, this paper improves the Min-Min algorithm and proposes trust model-based Min-Min scheduling algorithm. This algorithm consists of three phases: data file selecting, task scheduling and data scheduling. Two salient features of this algorithm are: 1) in selecting task-required data files, it considers file server's trust degree and data transmission time, it selects the data file with bigger trust value and smaller data transmission time, 2) in data transmission time calculating and transmission path selecting, it adopts the shortest path algorithm-Dijkstra. The experiment results show that although this scheduling algorithm extends the task completion time, the success rate of task execution is apparently raised. © 2011 IEEE.

引用

页码：227 / 233

页数：6

共 22 条

[1]

Foster I., Kesselman C., Tuecke S., The anatomy of the grid: Enabling scalable virtual organizations, International Journal of High Performance Computing Applications, 15, 3, pp. 200-222, (2001)

[2]

Foster I., Kesselman C., Et al., The Grid: Blueprint for A Future Computing Infrastructure[M], (1998)

[3]

Braun T.D., Siegel H.J., Beck N., Boloni L.L., Maheswaran M., Reuther A.I., Robertson J.P., Theys M.D., Yao B., Hensgen D., Freund R.F., A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems, Journal of Parallel and Distributed Computing, 61, 6, pp. 810-837, (2001)

[4]

Biegel J.E., Davern J.J., Genetic algorithms and job shop scheduling, Computers & Industrial Engineering, 19, 1-4, pp. 81-91, (1990)

[5]

Steinhofel K., Albrecht A., Wong C.K., Two simulated annealingbased heuristics for the job scheduling problem, Operational Research, 118, 3, pp. 524-548, (1999)

[6]

Maheswaran M., Ali S., Jay Siegel H., Et al., Dynamic matching and scheduling of a class of independent tasks onto heterogeneous computing systems[A], Proceedings of the 8th IEEE Heterogeneous Computing Workshop[C], April 12, 1999, pp. 30-44

[7]

Etminani K., Naghibzadeh M., A Min-Min Max-Min selective algorithm for grid task scheduling[A], Proceedings of 3rd IEEE/IFIP International Conference in Central Asia on Internet[C], September 26-28, 2007, Tashkent, Uzbekistan

[8]

Cao H., Jin H., Wu X., Et al., DAGMap: Efficient scheduling for DAG grid workflow job[A], Proceedings of 9th IEEE/ACM International Conference of Grid Computing[C], September 29-October 1, 2008, pp. 17-24

[9]

Wang X., Buyya R., Su J., Reliability-Oriented Genetic Algorithm for Workflow Applicaions Using Max-Min Stragegy[A], Proceedings of 9th IEEE/ACM International Symposium on Cluster Computing and the Grid[C], May 18-21, 2009, pp. 108-115

[10]

Bell W.H., Cameron D.G., Carvajal-Schiaffino R., Et al., Evaluation of an economy-based file replication strategy for a data grid[A], Proceedings of the 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid[C], May 12-15, 2003, pp. 52-59

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