Object-as-a-Service (OaaS): A Mixed Method Approach to Balance Computational Overheads in Serverless Cloud Computing

Cloud computing exponentially demands novel architectural approaches that are capable of satisfying scalability, resource efficiency, and dynamic service provisioning. Even with serverless computing's positive advancements, the paradigms that have been developed thus far have problems allocating granular resources, handling permanent objects, and attaining elasticity without interruption-especially in complicated, data-intensive applications. This study introduces the concept of Object-as-a-Service (OaaS), a paradigm-shifting model of cloud computing that essentially reframes the provisioning, management, and consumption of computational objects. The study further explored OaaS's potential to overcome the limitations of traditional serverless computing through a comprehensive mixed-method approach that combines empirical modeling, large-scale simulation, and prototype implementation. The proposed methodology relies on advanced performance benchmarking across workloads that trace detailed resource utilization patterns for computational workloads. Experimental results showed that OaaS can save up to 37 % in infrastructure overhead while maintaining 94.6 % greater resource utilization over conventional serverless architectures. It reveals key findings in the superior capabilities of OaaS for dynamic object lifecycle management, which leads to unprecedented levels of computational granularity and efficiency.