A Novel Methodology for Capitalizing on Cloud Storage through a Big Data-as-a-Service Framework
Georgios Skourletopoulos , Constandinos X. Mavromoustakis , George Mastorakis , Periklis Chatzimisios , Jordi Mongay Batalla
AbstractThe 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 cloud- inspired quantitative cost and benefits analysis models under the assumption that the demand curves are linear. The proposed modelling approach is evaluated against the conventional high- performance data warehouse appliances on the necessity of possible upgradation of the storage.
|Publication size in sheets||0.5|
|Book||Proceedings of the 2016 IEEE Globecom Workshops - GC Workshops 2016, 2016, IEEE, ISBN 978-1-5090-2482-7, [978-1-5090-2483-4], 1600 p., DOI:10.1109/GLOCOMW.2016.7848796|
|Keywords in English||Cloud computing, Cost benefit analysis, Analytical models, Data models, Business, Data warehouses, Big data|
|Project||ID-based Secure COMmunications system for unified access in IoT. Project leader: Krawiec Piotr,
, Phone: +48 22 234 7231, start date 01-04-2014, planned end date 31-03-2017, end date 31-05-2017, IT/2014/badawczy/40, Completed
|Score|| = 15.0, 05-03-2020, BookChapterMatConfByIndicator|
= 15.0, 05-03-2020, BookChapterMatConfByIndicator
|Publication indicators||= 3; = 1; = 4.0|
|Citation count*||4 (2020-07-05)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.