主讲人简介：美国北岸社区学院计算机科学系教授，同时任教于美国东北大学
讲座摘要：
Distributed cloud computing and Peer-to-Peer (P2P) systems have emerged as an active research field that
combines techniques which cover networks, distributed computing, distributed database,
and the various distributed applications.Distributed cloud computing and P2P systems scale to voluminous
information on very large numbers of
participating nodes in distributed systems. Data mining on large distributed databases is a very
important research area. Traditional data mining approach on a single machine or client-server network model does not satisfy the requirements from the large distributed databases and
applications in cloud computing systems. Two important challenges are raised, one is how to
implement data mining for large distributed databases in cloud computing systems, and the other is
how to develop parallel data mining algorithms and software tools for the distributed cloud computing
systems to improve the efficiency.In this talk, a design and implementation of a parallel data mining
algorithm in a P2P cloud computing system is presented and discussed in detail, which satisfies the
distribution of the cloud computing system well and makes parallel cloud computing become true.
The performance and comparison of the parallel algorithm with the sequential algorithm is analyzed
and evaluated, which presents the parallel algorithm features consistent implementation, higher
performance, and fine scalable ability.
