An improved multilevel resource handling strategy for cloud based video streaming
Video data transmission and video streaming allows people to access the stored video media using the network
anywhere in the world. An adaptive scheme is applied to perform the resource allocation in terms of
bandwidth and video memory in cloud-based video streaming. Advances and commoditization of media
generation devices enable capturing and sharing of any special event by multiple attendees. Video streaming is
multimedia that is constantly received by and presented to an end-user while being delivered by a video service
provider or sender. With the rapid development of cloud technology, many services have been transferred from
local computers to the cloud-based platform, which decreases the amount of computation done on the former.
Graphics processing, apart from providing user interfaces featuring diversified special effects, is also significant
in terms of application programs and play interactions. The proposed model combines a QoS aware resource
allocation strategy for mobile 3D graphics rendering, which is a hybrid rendering technology combining the
client-side graphics processing capabilities with the graphics processing units on the cloud-based platform. The
proposed system is called Graphics Adaptive Resource Allocation Strategy (GARAS), and it delivers multiple
views of an event to viewers at the best possible video representation based on each viewer’s available
bandwidth GARAS is a complex system having many research challenges. The objective of the study is to
maximize the overall viewer satisfaction by allocating available resources to transcode views in an optimal set
of representations, subject to computational and bandwidth constraints.
