P2P Algorithm Study For Massive Data Dispatch Of WebVR Platform

WebVR, which is the combination of two most promising computer technologies Web and Virtual Reality (VR), has attracted much attention in recent years thanks to its novel mode of human-computer interaction and wide application prospects. Rapid advancements in computer graphics display technologies and hardware allow people to obtain more immersion in a virtual environment, however, the fluency of scene loading seriously suffers because of the massive data plus limited bandwidth resulted from the increasing area of virtual scene. Based on the replacement of traditional network architecture and optimization of data storage as well as effective management of large-scale users, this paper focuses on the P2P algorithm study for massive data schedule of WebVR platform. The main contents can be summarized as follows:1. Studies the novel virtual scene dispatch scheme based on Peer-to-Peer (P2P) network, including data encryption, release, index, uploading, downloading and sharing, which provides a new pattern of obtaining data and compensates the demerits exist in B/S and C/S framework.2. Investigates and implements the efficient management of massive users through modified Kademlia algorithm. Furthermore, functional modules such as creating contact routing list, adding buddies, information sharing and instant messaging are realized, which further explores the potential in terms of user scalability and neighbor consistency in distributed virtual environment.3. Makes a preliminary study on applying the data dispatch strategy based on P2P architecture to the WebVR platform, achieving ideal efficiency of data transmission and user management effectiveness.The key technologies and algorithms this paper referred have been integrated into the WebVR platform developed by the laboratory and the correctness and reliability have been verified by the experimental results and applications.