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Big Data-Oriented PaaS Architecture with Disk-as-a-Resource Capability and Container-Based Virtualization
(Springer Netherlands, 2018-12)
[Abstract] With the increasing adoption of Big Data technologies as basic tools for the ongoing Digital Transformation, there is a high demand for data-intensive applications. In order to efficiently execute such applications, ...
BDWatchdog: real-time monitoring and profiling of Big Data applications and frameworks
(Elsevier BV * North-Holland, 2018-10)
[Abstract] Current Big Data applications are characterized by a heavy use of system resources (e.g., CPU, disk) generally distributed across a cluster. To effectively improve their performance there is a critical need for ...
Enhancing in-memory Efficiency for MapReduce-based Data Processing
(Academic Press, 2018-10)
[Abstract] As the memory capacity of computational systems increases, the in-memory data management of Big Data processing frameworks becomes more crucial for performance. This paper analyzes and improves the memory ...
Analysis and evaluation of MapReduce solutions on an HPC cluster
(Pergamon Press, 2016-02)
[Abstract] The ever growing needs of Big Data applications are demanding challenging capabilities which cannot be handled easily by traditional systems, and thus more and more organizations are adopting High Performance ...
Flame-MR: An event-driven architecture for MapReduce applications
(Elsevier BV * North-Holland, 2016)
[Abstract] Nowadays, many organizations analyze their data with the MapReduce paradigm, most of them using the popular Apache Hadoop framework. As the data size managed by MapReduce applications is steadily increasing, the ...
Performance Evaluation of Big Data Frameworks for Large-Scale Data Analytics
(IEEE Computer Society, 2017-02-06)
[Abstract] The increasing adoption of Big Data analytics has led to a high demand for efficient technologies in order to manage and process large datasets. Popular MapReduce frameworks such as Hadoop are being replaced by ...
MREv: An Automatic MapReduce Evaluation Tool for Big Data Workloads
(Elsevier, 2015)
[Abstract]: The popularity of Big Data computing models like MapReduce has caused the emergence of many frameworks oriented to High Performance Computing (HPC) systems. The suitability of each one to a particular use case ...
MarDRe: efficient MapReduce-based removal of duplicate DNA reads in the cloud
(Oxford University Press, 2017)
[Abstract] This article presents MarDRe, a de novo cloud-ready duplicate and near-duplicate removal tool that can process single- and paired-end reads from FASTQ/FASTA datasets. MarDRe takes advantage of the widely adopted ...
SMusket: Spark-based DNA error correction on distributed-memory systems
(Elsevier B.V., 2020)
[Abstract]: Next-Generation Sequencing (NGS) technologies have revolutionized genomics research over the last decade, bringing new opportunities for scientists to perform groundbreaking biological studies. Error correction ...
Real-time resource scaling platform for Big Data workloads on serverless environments
(2020)
The serverless execution paradigm is becoming an increasingly popular option when workloads are to be deployed in an abstracted way, more specifically, without specifying any infrastructure requirements. Currently, such ...