Open Access Repository
Programming SDN-Native big data applications: research gap analysis
Altmetric
Altmetric
Altmetric
Alwasel, K, Li, Y, Jayaraman, PP, Garg, SK 
ORCID: 0000-0003-3510-2464, Calheiros, RN and Ranjan, R 2017
, 'Programming SDN-Native big data applications: research gap analysis'
, IEEE Cloud Computing, vol. 4, no. 5
, pp. 62-71
, doi: 10.1109/MCC.2017.4250934.
ORCID: 0000-0003-3510-2464, Calheiros, RN and Ranjan, R 2017
, 'Programming SDN-Native big data applications: research gap analysis'
, IEEE Cloud Computing, vol. 4, no. 5
, pp. 62-71
, doi: 10.1109/MCC.2017.4250934.
Full text not available from this repository.
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 Type: | Article |
|---|---|
| Authors/Creators: | Alwasel, K and Li, Y and Jayaraman, PP and Garg, SK and Calheiros, RN and Ranjan, R |
| Keywords: | SDN, big data |
| Journal or Publication Title: | IEEE Cloud Computing |
| Publisher: | IEEE Computer Society |
| ISSN: | 2325-6095 |
| DOI / ID Number: | 10.1109/MCC.2017.4250934 |
| Copyright Information: | © 2017 IEEE |
| Related URLs: | |
| Item Statistics: | View statistics for this item |
Actions (login required)
 |
Item Control Page |