Qos-Aware Video Streaming based Admission Control and Scheduling for Video Transcoding in Cloud Computing

Power and other computing resources can be stored and processed in cloud computing environments. Depending on the features of the clients' devices, video streams, whether they are live or on-demand, often need to be transcoded or converted (such as supported formats, bandwidth, and spatial resolution, for example). Currently, streaming service providers maintain multiple transcoded versions of the same video to serve various client devices because transcoding is a computationally expensive and time-consuming process. To eliminate jitters in accepted streams while transcoding, a task scheduling mechanism is included. To ensure that the consumer receives continuous video content delivery, this technique involves cutting a tiny number of video frames from a video segment. In this evaluation, admission control and scheduling based on QoS -aware video streams is the new task scheduling method for video recording that is suggested. With the help of this framework, streaming platform services have made efficient use of cloud resources while following to the Quality of Service (QoS) standards for video transmissions. The technologies are advancing a scheduling technique that is QoS -aware to effectively map video streams to cloud resources in order to deliver high QoS. The performance of this analysis is calculated on different aspects such as Accuracy, Qos and Recall. In this approach the QoS -aware video streaming based admission control and scheduling for video transcoding in cloud computing will give the best outcomes.