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Programming SDN-Native big data applications: research gap analysis


Alwasel, K and Li, Y and Jayaraman, PP and Garg, SK and Calheiros, RN and Ranjan, R, Programming SDN-Native big data applications: research gap analysis, IEEE Cloud Computing, 4, (5) pp. 62-71. ISSN 2325-6095 (2017) [Refereed Article]

Copyright Statement

2017 IEEE

DOI: doi:10.1109/MCC.2017.4250934


Software-Defined Networking has involved as a preferred abstraction for sharing network resources within a cloud datacenter in response to simultaneous data retrieval and computation demands from around the world. However, several research challenges need to be investigated before SDN powered-cloud datacenters are able to efficiently process big data as defined by its "4V" characteristics. Big data enabled systems have to be able to respond to concurrent requests and allocate computing (e.g., virtual machine instances), storage (e.g., disk space) and networking (e.g., bandwidth) resources efficiently and effectively.

Item Details

Item Type:Refereed Article
Keywords:SDN, big data
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Distributed systems and algorithms
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Garg, SK (Dr Saurabh Garg)
ID Code:124815
Year Published:2017
Web of Science® Times Cited:4
Deposited By:Information and Communication Technology
Deposited On:2018-03-13
Last Modified:2018-12-13

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