Big Data in Cloud Computing: features and issues
Pedro Caldeira Neves,
Bradley Schmerl, Jorge Bernardino and
Javier Cámara.
In Proceedings of the 2016 International Conference on Internet of Things and Big Data, Rome, Italy, 23-25 April 2016.
Online links:
Abstract
The term big data arose under the explosive increase of global data as a technology that is able to store and process big and varied volumes of data, providing both enterprises and science with deep insights over its clients/experiments. Cloud computing provides a reliable, fault-tolerant, available and scalable environment to harbour big data distributed management systems. Within the context of this paper we present an overview of both technologies and cases of success when integrating big data and cloud frameworks. Although big data solves much of our current problems it still presents some gaps and issues that raise concern and need improvement. Security, privacy, scalability, data governance policies, data heterogeneity, disaster recovery mechanisms, and other challenges are yet to be addressed. Other concerns are related to cloud computing and its ability to deal with exabytes of information or address exaflop computing efficiently. This paper presents an overview of both cloud and big data technologies describing the current issues with these technologies. |
Keywords: Big data.
@InProceedings{2016/Neves/IoTBD,
AUTHOR = {Neves, Pedro Caldeira and Schmerl, Bradley and Bernardino, Jorge and C\'{a}mara, Javier},
TITLE = {Big Data in Cloud Computing: features and issues},
YEAR = {2016},
MONTH = {23-25 April},
BOOKTITLE = {Proceedings of the 2016 International Conference on Internet of Things and Big Data},
ADDRESS = {Rome, Italy},
PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/IoTBD_2016_10.pdf},
ABSTRACT = {The term big data arose under the explosive increase of global data as a technology that is able to store and process big and varied volumes of data, providing both enterprises and science with deep insights over its clients/experiments. Cloud computing provides a reliable, fault-tolerant, available and scalable environment to harbour big data distributed management systems. Within the context of this paper we present an overview of both technologies and cases of success when integrating big data and cloud frameworks. Although big data solves much of our current problems it still presents some gaps and issues that raise concern and need improvement. Security, privacy, scalability, data governance policies, data heterogeneity, disaster recovery mechanisms, and other challenges are yet to be addressed. Other concerns are related to cloud computing and its ability to deal with exabytes of information or address exaflop computing efficiently. This paper presents an overview of both cloud and big data technologies describing the current issues with these technologies.},
KEYWORDS = {Big data} }
|