How Distributed Data Mining Tasks can Thrive as Knowledge Services

被引：24
|
作者：
Talia, Domenico [1 ,2 ]
Trunfio, Paolo [1 ]
机构：
[1] Univ Calabria, I-87030 Commenda Di Rende, Italy
[2] CNR, Inst High Performance Comp & Networking ICAR, I-00185 Rome, Italy
来源：
COMMUNICATIONS OF THE ACM | 2010年 / 53卷 / 07期
关键词：
GENERATION; GRIDS;
D O I：
10.1145/1785414.1785451
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Grid and Cloud computing are evolved models of distributed computing and parallel processing technologies. The grid is a distributed computing infrastructure that enables coordinated resource sharing within dynamic organizations consisting of individuals, institutions, and resources. The grid community has adopted the Open Grid Services Architecture (OGSA) as an implementation of the service-oriented architecture (SOA) model within the Grid context. The collection of data mining services constitutes an Open Service Framework for grid-oriented data mining that allow developers to design distributed knowledge discovery in databases (KDD) processes as a composition of single services that are available over Grids. Weka is a widely used open source data mining toolkit that runs on a single machine. Weka-4WS integrates Weka and the WS-Resource Framework (WSRF) technology for running remote data mining algorithms and managing distributed computations as workflows. The Weka4WS user interface supports the execution of both local and remote data mining tasks.
引用
收藏
页码：132 / 137
页数：6
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