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Programming SDN-Native big data applications: research gap analysis

Citation

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

Abstract

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
Research Field:Distributed and Grid Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
UTAS Author:Garg, SK (Dr Saurabh Garg)
ID Code:124815
Year Published:2017
Deposited By:Information and Communication Technology
Deposited On:2018-03-13
Last Modified:2018-12-13
Downloads:0

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