Cost Optimization in Cloud Computing

doi:10.23940/ijpe.26.01.p1.19

Abstract

Abstract: Cloud computing is an integral part of modern computational activities, offering on-demand resources via SaaS, PaaS, IaaS, and diverse deployment models. Cost management remains a key focus amid resource constraints. This paper explores cloud cost optimization, defining total cost as the sum of migration, downtime, operational overhead, execution, and communication costs with corresponding mathematical formulations. It classifies optimization techniques into static (advance resource allocation) and dynamic (pay-as-you-go) approaches, detailing methods like genetic algorithms and approximate dynamic programming. Practical cost-cutting strategies are proposed, including auto-scaling, optimized data transfer, high-availability architectures, and managed services. Priority factors for optimization include scheduling, demand trace, and reliability. Effective optimization enhances resource utilization, reduces costs, and boosts cloud system profitability and stability.

Key words: cloud computing, cost optimization, resource provisioning, optimization techniques, cost metrics

Peng Hu and Nengyue Su. Cost Optimization in Cloud Computing [J]. Int J Performability Eng, 2026, 22(1): 1-9.

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