An efficient caching algorithm for peer-to-peer 3D streaming in distributed virtual environments
An efficient caching algorithm for peer-to-peer 3D streaming in distributed virtual environments
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DOI：
10.1016/j.jnca.2014.03.005
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发表时间：
2014-06
期刊：
影响因子：
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通讯作者：
Jinyuan Jia;Wei Wang;Xiaojun Hei
中科院分区：
文献类型：
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作者：
Jinyuan Jia;Wei Wang;Xiaojun Hei
近年来，随着互联网和虚拟现实技术的发展，分布式虚拟环境（DVE）的应用越来越广泛。在DVE中，高分辨率的3D内容可能会生成大量数据，而对等（P2P）流媒体则利用这些优势以具有成本效益的方式承载这些巨大的流量。在这种P2P模式中，节点可以协同缓存和共享DVE数据，以减少服务器的工作负载并提高流媒体质量。然而，有效地维护和更新每个对等体中的缓存内容是至关重要的。在本文中，我们提出了一个高效的缓存算法的P2P 3D内容流框架。建议的缓存算法是基于一个新的保存度量，该度量被定义为平衡视觉显着性，可重用性和潜在的相关性缓存的3D对象。然后，这些缓存的3D对象在每个对等体中更新自适应的上升顺序的重要性量化使用这个新的度量。我们在一个模拟的DVE平台上实现了基于P2P的3D流媒体缓存算法。我们进行了全面的模拟研究，我们的实验结果表明，建议的对等流媒体方法优于经典的3D流媒体方法（包括FLoD和MRM）的填充率，基本延迟，节点的请求和服务器的请求。
Recent technical progress on the Internet and virtual reality has enabled the proliferation of the applications of distributed virtual environments (DVEs). In a DVE, high-resolution 3D contents may generate huge data while 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 implemented 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 classic 3D streaming methods (including FLoD and MRM) in terms of fill ratio, base latency, requests by nodes and requests to the server.