کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
865455 | 909668 | 2010 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Concurrent and Storage-Aware Data Streaming for Data Processing Workflows in Grid Environments
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موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی (عمومی)
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Data streaming applications, usually composed of sequential/parallel data processing tasks organized as a workflow, bring new challenges to workflow scheduling and resource allocation in grid environments. Due to the high volumes of data and relatively limited storage capability, resource allocation and data streaming have to be storage aware. Also to improve system performance, the data streaming and processing have to be concurrent. This study used a genetic algorithm (GA) for workflow scheduling, using on-line measurements and predictions with gray model (GM). On-demand data streaming is used to avoid data overflow through repertory strategies. Tests show that tasks with on-demand data streaming must be balanced to improve overall performance, to avoid system bottlenecks and backlogs of intermediate data, and to increase data throughput for the data processing workflows as a whole.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Tsinghua Science & Technology - Volume 15, Issue 3, June 2010, Pages 335-346
Journal: Tsinghua Science & Technology - Volume 15, Issue 3, June 2010, Pages 335-346
نویسندگان
Wen (å¼ æ), Junwei (æ¹åå¨), Yisheng (éå®ç), Lianchen (åè¿è£), Cheng (å´ æ¾),