Partitioning the Impact of Mobile Applications on Big Data Cloud

Partitioning the Impact of Mobile Applications on Big Data Cloud

Big Data Cloud

Mobile Application

Transaction per Second

Abstract: Inception of mobile devices and applications have seen an exponential growth of data. Bandwidth limitation for cloud-hosted applications is the “Elephant in the room”. This research has designed an algorithm to address the bandwidth limitations by data prioritizing and partitioning. Saudi Arabia is developing a financial district in Riyadh that could serve as financial hub for the region and could help Saudi Arabia to enter the domain of developed countries. Inception of cloud technology could play a key role for financial institutions for resource gathering and allocation. The research has formulated a priority sequence queuing model that filters the incoming cloud bundles based on their priority defined by the business logic. The research has designed a novel and secure E-Banking solution that is already been implemented for Canadian Imperial Bank of Commerce (CIBC) and if adapted for the oil rich nation i.e. Saudi Arabia, can foster the growing consumer market for changing global priorities. User access through both desktop/laptop and mobile applications present a challenging scenario for the cloud server hosting multiple sessions. The Transaction per Second (TPS) and multiple sessions hit ratio can create a system overhead which is hard to predict and calculate, and can run the cloud server down. In addition to queuing algorithm the research has also implemented a session Time to Live (TTL), cross session check and kill algorithm, which is also based on business logic. It is assumed that a single customer could hold multiple logins on a database cloud server utilizing a single push and multiple pull mechanism for online, Automated Business Machine and mobile devices.

1041-1046

109

Ahmed, Fayyaz

8th International Conference on Ambient Systems, Networks and Technologies, ANT-2017 and the 7th International Conference on Sustainable Energy Information Technology, SEIT 2017, 16-19 May 2017, Madeira, Portugal

2017

journalArticle

1877-0509

10.1016/j.procs.2017.05.423