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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 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: | 2 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2018-03-13 |
| Last Modified: | 2018-12-13 |
| Downloads: | 0 |
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