The computing demand for massive applications has led to the ubiquitous deployment of
computing power. This trend results in the urgent need for higher-level computing resource …

In the era of global-scale services, organisations produce huge volumes of data, often
distributed across multiple data centres, separated by vast geographical distances. While …

Big data frameworks such as Apache Spark is becoming prominent to perform large-scale
data analytics jobs in various domains. However, due to limited resource availability, the …

Bottleneck issues handled in the field of information retrieval are analysis of query and
management of data storage. Hadoop is a large scale environment that is supported with …

Multilevel parallelism hierarchy is a key feature of modern parallel computing platforms. It
adds a vertical dimension of heterogeneity, which, together with the horizontal heterogeneity …

In the era of global-scale services, organisations produce huge volumes of data, often
distributed across multiple data centres, separated by vast geographical distances. While …

Analyzing a vast amount of business and user data on big data analytics frameworks is
becoming a common practice in organizations to get a competitive advantage. These …

The ability to aggregate the computational resources of multiple clusters is useful for solving
large problems that can benefit from multicluster platforms. In this context, this paper …

MapReduce is a simple and elegant programming model suitable for loosely coupled
parallelization problems—problems that can be decomposed into subproblems. Hadoop …

Swirls is a general purpose application for interactive building, deploying, and execution of
message-passing parallel programs that address multicluster and multicloud requirements …