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Adaptive Performance for WoIP Implementation in Cloud Computing Environment

机译:云计算环境中WoIP实施的自适应性能

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In this paper we have implemented a real-time video/voice over IP (WoIP) applications on a Hadoop cloud computing system and it is denoted CLC-IHU. It really outperforms the previous WoIP using P2P connection (called SCTP-IHU) due to the easy-to-use and high-performance on video phone call. User does not need to know what is a real IP and web interface achieves interaction by adopt TCP instead of PR-SCTP so taht CLC-IHU scheme reduces computation load and power consumption dramatically at thin clients. We employed adaptive network-based fuzzy inference system (ANFIS) to tune key factors appropriately for adapting handoff and analyzing network traffic at any time. As a result it takes about 1.631 sec for the seamless handoff between base stations under mobile wireless network. In access control for preventing illegal intrusions from the outside of the cloud, the rapid facial recognition and fingerprint identification via cloud computing has been done successfully within 2.2 seconds to identify the subject exactly.
机译:在本文中,我们已经在Hadoop云计算系统上实现了IP实时视频/语音(WoIP)应用,并将其表示为CLC-IHU。由于视频电话的易用性和高性能,它确实优于以前的使用P2P连接的WoIP(称为SCTP-IHU)。用户无需知道什么是真正的IP,而Web接口通过采用TCP而不是PR-SCTP来实现交互,因此,这种CLC-IHU方案可显着减少瘦客户端的计算负荷和功耗。我们采用了基于自适应网络的模糊推理系统(ANFIS)来适当地调整关键因素,以适应切换并随时分析网络流量。结果,移动无线网络下基站之间的无缝切换大约需要1.631秒。在防止来自云外部的非法入侵的访问控制中,已成功在2.2秒内成功完成了通过云计算的快速面部识别和指纹识别,以准确识别对象。

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