General Sparse Matrix-Matrix Multiplication (SpGEMM) has attracted much attention from
researchers in graph analyzing, scientific computing, and deep learning. Many optimization …

Data centers for cloud computing must accommodate numerous parallel task executions
simultaneously. Therefore, data centers have many virtual machines (VMs). Minimizing the …

Performance optimization based on node attributes is of profound significance in the replica
placement algorithm used in Hadoop distributed file system (HDFS). Currently, most …

Cloud computing is becoming popular because it offers the pay-as-per-use model with
business benefits of enhanced scalability, flexibility, mobility and reliability with cost …

Sparse generalized matrix-matrix multiplication (SpGEMM) is a fundamental operation for
real-world network analysis. With the increasing size of real-world networks, the single …

As the complexity of workflow applications increase, the scheduling and execution of
workflow incur more waste of resources. In order to achieve load balancing and reduce the …

MapReduce is a common framework that effectively processes multi-petabyte data in a
distributed manner. Therefore, MapReduce is widely used in heterogeneous environments …

Due to the advent of new technologies, devices, and communication tools such as social
networking sites, the amount of data produced by mankind is growing rapidly every year. Big …

In the context of MapReduce task scheduling, many algorithms mainly focus on the
scheduling of Reduce tasks with the assumption that scheduling of Map tasks is already …

We study the problem of task reallocation for load-balancing of MapReduce jobs in
applications that process large datasets. In this context, we propose a novel strategy based …