Time is critical in the resource provisioning process in the Cloud Computing paradigm when serving cloud resources to cloud users. It's difficult for a cloud provider to serve a large number of users while also reducing long wait times after they've submitted a request. It is possible to improve the time factor by using a systematic resource provisioning process. This paper examines several time-based resource provisioning frameworks in greater detail. Many researchers focused on various time parameters that assist cloud service providers in providing the best resource-serving services to their customers. The primary goal of this paper is to assist future researchers, as well as cloud providers in observing and selecting the best time-based resource provisioning technique also they can emphasize building a new dynamic resource provisioning paradigm in the future with this work’s observations. To validate these observations, a novel Particle Swarm Optimization (PSO) based model is designed in this text, which uses the selected time-based resource provisioning technique, and applies it to real-time cloud scenarios. It was observed that the proposed model was able to showcase better efficiency of scheduling, and optimum cloud utilization when compared with other time-based resource provisioning models for different cloud deployments