Open AccessA Novel Optimization of Cloud Instances with Inventory Theory Applied on Real Time IoT Data of Stochastic Nature
Author(s) -
Sayan Guha
Publication year - 2021
Publication title -
international journal of cloud computing : service and architecture/international journal of cloud computing : services and architecture
Language(s) - English
Resource type - Journals
eISSN - 2231-6663
pISSN - 2231-5853
DOI - 10.5121/ijccsa.2021.11603
Subject(s) - cloud computing , workload , computer science , range (aeronautics) , architecture , mathematical optimization , operations research , industrial engineering , mathematics , engineering , art , visual arts , aerospace engineering , operating system
A Horizontal scaling is a Cloud architectural strategy by which the number of nodes or computers increased to meet the demand of continuously increasing workload. The cost of compute instances increases with increased workload & the research is aimed to bring an optimization of the reserved Cloud instances using principles of Inventory theory applied to IoT datasets with variable stochastic nature. With a structured solution architecture laid down for the business problem to understand the checkpoints of compute instances – the range of approximate reserved compute instances have been optimized & pinpointed by analysing the probability distribution curves of the IoT datasets. The Inventory theory applied to the distribution curves of the data provides the optimized number of compute instances required taking the range prescribed from the solution architecture. The solution would help Cloud solution architects & Project sponsors in planning the compute power required in AWS® Cloud platform in any business situation where ingestion & processing data of stochastic nature is a business need.