Granules: A Lightweight, Streaming Runtime for Cloud Computing With Support for Map-Reduce

被引:0
|
作者
Pallickara, Shrideep [1 ,2 ]
Ekanayake, Jaliya [2 ]
Fox, Geoffrey [2 ]
机构
[1] Colorado State Univ, Dept Comp Sci, Ft Collins, CO 80523 USA
[2] Indiana Univ, Community Grids Lab, Bloomington, IN 47405 USA
关键词
map-reduce; cloud computing; streaming; cloud runtimes; content distribution networks;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing has gained significant traction in recent years. The Map-Reduce framework is currently the most dominant programming model in cloud computing settings. In this paper, we describe Granules, a lightweight, streaming-based runtime for cloud computing which incorporates support for the Map-Reduce framework. Granules provides rich lifecycle support for developing scientific applications with support for iterative, periodic and data driven semantics for individual computations and pipelines. We describe our support for variants of the Map-Reduce framework. The paper presents a survey of related work in this area. Finally, this paper describes our performance evaluation of various aspects of the system, including (where possible) comparisons with other comparable systems.
引用
收藏
页码:326 / +
页数:2
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