Cost Efficiency In Server-Less Computing Using Queueing Models With Cloud Services
Abstract
This paper examines cost efficiency in server-less architectures using queueing models across various types of cloud services, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Function as a Service (FaaS). By modeling these environments as queueing systems, we analyze how different service types, request arrival rates, execution times, and resource provisioning strategies impact cost and performance. Our findings reveal that each cloud service type offers unique cost advantages depending on the workload characteristics and that careful optimization of resource allocation and request management can lead to significant cost savings. The study provides actionable insights for organizations looking to optimize their cloud service usage, offering a comparative analysis that guides the selection of the most cost-effective server-less solutions tailored to specific application needs. Serverless computing has become a popular approach for deploying applications due to its scalability and reduced infrastructure management.
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