When you think about how far and fast computer science has progressed in recent years, it's
not hard to conclude that a seven-year old handbook may fall a little short of the kind of …

One of the most successful techniques in large-scale data-intensive computations is
MapReduce programming. MapReduce is based on a divide and conquer approach that …

Data replication is a practical and effective method to achieve efficient and fault-tolerant data
access in grids. Traditionally, data replication schemes maintain an entire replica in each …

The InfiniBand architecture is among the leading interconnects that support high
performance computing. The high bandwidth and low latency provided by InfiniBand are …

Applications that explore, query, analyze, visualize, and, in general, process very large scale
data sets are known as Data Intensive Applications. Large scale data intensive computing …

Data mining and knowledge discovery is a fast growing field of study. Numerous
applications of data mining are reported on various domains. Due to significant …

Abstract Traditional High-Performance Computing (HPC) based big-data applications are
usually constrained by having to move large amount of data to compute facilities for real …

Data Grid is a geographically distributed environment that deals with large-scale data-
intensive applications. Effective scheduling in Grid can reduce the amount of data …

With the increasing data size in materials science, existing programming models no longer
satisfy the application requirements. MapReduce is a programming model that enables the …

Data replication is one of the mechanisms in data grid architecture since it improves data
access and reliability. There are many replication techniques exist in distributed systems …