Grid computing is a form of distributed computing that involves coordinating and sharing computational power, data storage and network resources across dynamic and geographically dispersed organizations.Grid computing is a term referring to the combination of computer resources from multiple administrative domains to reach a common goal. The resources in the Grid are heterogeneous and geographi...

With the evolution of geographically distributed data centers in Cloud Computing landscape along with amount being processed these centers, which is growing at an exponential rate, processing massive applications become important topic. Since a given task may require many datasets for its execution and are spread over several different finding efficient way to manage storage across nodes system...

Hadoop and Spark are widely used distributed processing frameworks for large-scale data processing in an efficient and fault-tolerant manner on private or public clouds. These big-data processing systems are extensively used by many industries, e.g., Google, Facebook, and Amazon, for solving a large class of problems, e.g., search, clustering, log analysis, different types of join operations, m...

Many industrial, scientific, and commercial applications need to analyze large data sets maintained over geographically distributed sites. The geographic distribution and the large amount of data involved often oblige designers to use distributed and parallel systems. The Grid can play a significant role in providing an effective computational support for distributed data mining and knowledge d...