As the demands for big data analytics keep growing rapidly in scientific applications and
online services, MapReduce and its open-source implementation Hadoop gained popularity …

A MapReduce scheduling algorithm plays a critical role in managing large clusters of
hardware nodes and meeting multiple quality requirements by controlling the order and …

The MapReduce (MR) scheduling is a prominent area of research to minimize energy
consumption in the Hadoop framework in the era of green computing. Very few scheduling …

The volume of generated data increases by the rapid growth of Internet of Things, leading to
the big data proliferation and more opportunities for datacenters. Highly virtualized cloud …

With the explosion of data production, the efficiency of data management and analysis has
been concerned by both industry and academia. Meanwhile, more and more energy is …

The use of economical, low-power microservers comprising of embedded CPUs is on the
rise in supporting a myriad of applications. State of the art microservers can already match …

Emerging big data applications require a significant amount of server computational power.
However, the rapid growth in the data yields challenges to process them efficiently using …

MapReduce (MR) computing paradigm and its open source implementation Hadoop have
become a de facto standard to process big data in a distributed environment. Initially, the …

An approach and a method for efficient execution of nested map-reduce framework
workloads to take advantage of the combined execution of central processing units (CPUs) …

BACKGROUND A data center is a facility used to house computer systems, Such as servers,
and associated components. Such as telecom munications and storage systems. A data …