Optimize spot instance bidding strategies using nar neural network.

Infrastructure as a service is a core part of the cloud computing service model and cloud service providers. It is a type of cloud computing service model that allocates instant virtual computing infrastructure or network and storage resources to the customer's on-demand over the Internet. The cloud service providers aim to offer the best quality of service at the lowest price. The COVID-19 impact has fundamentally altered how companies utilize the IT infrastructure. That is, the 'work from home culture has increased every organization's dependency on cloud resources evermore. With many cloud service providers in the IT market, pricing is one of the critical factors determining its demand among cloud users and its position in the market. A cloud-pricing model affects customer behavior. Hence, deciding an optimum economic model for IaaS will attract more customers and achieve higher revenues for service providers. At present, cloud service providers like Amazon provide discount offers for their cloud resources in the form of spot instances that allows cloud users to take advantage of the available unused resources at low price on demand. These instances are purchased through a bidding process where the bid price is compared with the time-varying spot price. Given this background, the research paper will focus on studying how predictive analytics can analyze the trend in the time-variant spot price and predict making effective bids and purchasing the cloud resources at the best price. [ABSTRACT FROM AUTHOR]