Abstract
The Big Data-as-a-Service (BDaaS) framework exploits the elastic scalability and analytical data processing capabilities delivered via the cloud, minimizing the complexity and capital expense of on-premises data infrastructure. Since the cloud can be considered as a marketplace, small and large enterprises lease storage and computing capacity based on a negotiated cost approach. In this context, this research work examines a novel methodology for capitalizing earnings on cloud storage level through a big data-as-a-service framework and proposes cloudinspired quantitative cost and benefits analysis models under the assumption that the demand curves are linear. The proposed modelling approach is evaluated against the conventional highperformance data warehouse appliances on the necessity of possible upgradation of the storage.
Original language | English |
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Title of host publication | 2016 IEEE Globecom Workshops, GC Wkshps 2016 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781509024827 |
DOIs | |
Publication status | Published - 2016 |
Event | 2016 IEEE Globecom Workshops, GC Wkshps 2016 - Washington, United States Duration: 4 Dec 2016 → 8 Dec 2016 |
Other
Other | 2016 IEEE Globecom Workshops, GC Wkshps 2016 |
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Country/Territory | United States |
City | Washington |
Period | 4/12/16 → 8/12/16 |
Keywords
- Big Data-as-a-Service
- Cloud storage
- Cost-benefit analysis
- Data warehouse
- Linear modelling
- Mobile cloud computing