Balance visual saliency, reusability and potential relevance for caching P2P 3D streaming contents
Wei Wang, Jinyuan Jia, Xiaojun Hei · 2013
Recent technical progress on the Internet and virtual reality has enabled the proliferation of distributed virtual environments (DVEs). In a DVE, high-resolution 3D contents may generate huge data, and the peer-to-peer (P2P) streaming takes advantages to carry these huge traffic in a cost-effective manner. In this P2P paradigm, peers can cache and share DVE data cooperatively to reduce server workload and improve streaming quality. Nevertheless, it is critical to maintain and update the cached contents in each peer efficiently. In this paper, we propose an efficient caching algorithm for a P2P 3D content streaming framework. The proposed caching algorithm is based on a new preservation metric that is defined for balancing visual saliency, reusability and potential relevance of cached 3D objects. Then these cached 3D objects in each peer are updated adaptively with the ascendant order in importance quantified using this new metric. We implement the proposed caching algorithm in a simulated DVE platform for P2P-based 3D streaming. We conducted a comprehensive simulation study and our experimental results demonstrate that the proposed peer-to-peer streaming method outperforms the state-of-the-art 3D streaming methods (including FLoD and MRM) in the terms of fill ratio, base latency, requests by nodes and requests to the server.