TY - JOUR
T1 - Towards an Architecture for Handling Big Data in Oil and Gas Industries: Service-Oriented Approach
AU - Azzedin, Farag Ahmed Mohammad
AU - Ghaleb, M
PY - 2019
Y1 - 2019
N2 - Existing architectures to handle big data in Oil & gas industry are based on industry-specific platforms and hence limited to specific tools and technologies. With these architectures, we are confined to big data single-provider solutions. The idea of multi-provider big data solutions is essential. When building up big data solutions, organizations should embrace the best-inclass technologies and tools that different providers offer. In this article, we hypothesize that the limitations of the proposed big-data architectures for oil and gas industries can be addressed by a Service Oriented Architecture approach. In this article, we are proposing the idea of breaking complex systems to simple separate yet reliable distributed services. It should be noted that loose coupling exists between the interacting services. Thus, our proposed architecture enables petroleum industries to select the necessary services from the SOA-based ecosystem and create viable big data solutions.
AB - Existing architectures to handle big data in Oil & gas industry are based on industry-specific platforms and hence limited to specific tools and technologies. With these architectures, we are confined to big data single-provider solutions. The idea of multi-provider big data solutions is essential. When building up big data solutions, organizations should embrace the best-inclass technologies and tools that different providers offer. In this article, we hypothesize that the limitations of the proposed big-data architectures for oil and gas industries can be addressed by a Service Oriented Architecture approach. In this article, we are proposing the idea of breaking complex systems to simple separate yet reliable distributed services. It should be noted that loose coupling exists between the interacting services. Thus, our proposed architecture enables petroleum industries to select the necessary services from the SOA-based ecosystem and create viable big data solutions.
M3 - Article
SN - 2158-107X
JO - International Journal of Advanced Computer Science and Applications
JF - International Journal of Advanced Computer Science and Applications
ER -