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Access-Controlled Video/Voice over IP in Hadoop System with BPNN Intelligent Adaptation 1 Speaker : MA1G0222 2013.05.07 Authors:

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Outline INTRODUCTION VIDEO/VOICE OVER IP ON CLOUD COMPUTING REALIZATION OF CLOUD COMPUTING SYSTEM EMPIRICAL RESULTS AND DISCUSSIONS CONCLUSIONS 2

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INTRODUCTION Real-Time Transport Protocol (RTP) [1], relying on UDP, provides no loss recovery (unreliable). TCP protocol may cause long delay to get obsolete data at receiver side. In the previous work [2], the phone based on video/voice over IP (VVoIP) is established in ARM-based embedded platform rather than x86 machines [3] used in the earlier project. 3

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The objective is to ring a mobile phone call operated on P2P connection [4]. In order to tackle three crucial problems: headof- line blocking, handover interruption, and non-real-time transmission, we have adopted PR-SCTP protocol [5] instead of TCP. 4

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However, the computation load for real- time video phone call is so big and has caused ARM-based embedded platform [6] no longer with power-saving. Moreover, VVoIP need to know their respective IP address between two mobile devices before P2P connection. 5

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In order to resolve the problems as mentioned above, this study is to realize a real-time video/voice over IP (VVoIP) applications on Hadoop cloud computing [7] denoted CLCIHU. Next based on client/server architecture users employ web interface to achieve VVoIP connection and the phone call adopts an easy TCP-based RMTP connection instead of the complicated PR-SCTP because of web interface not supported by PR-SCTP. 6

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TCP UDP UDP TCP IETF (Internet Engineering Task Force) 2000 SCTP (Stream Control Transmission Protocol) TCP (multi-homing) SCTP (association) SCTP 2004 (partial reliable) PR-SCTP 7

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In terms of the quality of services (QoS), we have to tackle some of crucial problems about jitter, loss, latency, and throughput so as to maintain the smooth video/voice streaming over internet. We employed a back-propagation neural network (BPNN) [12] to tune parameters appropriately for adapting seamless handoff and analyzing network traffic over time. 8

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VIDEO/VOICE OVER IP ON CLOUD COMPUTING A number of remarkable cloud computing related firm, as we know, are indicated as follows: (a) public cloud like Google App Engine, Amazon Web Services, and Microsoft Azure; (b) private cloud like Microsoft MCloud, IBM Blue Cloud, and SalesForce.com; (c) open cloud : Open Nebula, Eucalyptus, Apache Hadoop, and NCDM Sector/Sphere; (d) hybrid cloud like IBM Blue Cloud. 9

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Two famous companies related to IP phone on cloud computing are voice over IP in a Cloud, IIS 2009 [13] and VoIP in cloud computing, Skpye in 2010 [14]. It has been set up in Hadoop cloud computing server [15][16] so that web interface is applicable to run and browse video phone call between cloud computing server and thin clients as shown in Fig. 1. 10

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REALIZATION OF CLOUD COMPUTING SYSTEM A. Deploying Hadoop cloud computin Once a Hadoop cloud computing has been established in server site, we have to test a number of seamless handoffs between clients and a Hadoop cloud computing system as shown in Fig. 2, 3, and 4. 12

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B. Establishing thin client and installing access control This study has chosen QT/Embedded framework instead of GTK series, in such a way that achieves GUI interface functions. Afterward QT/Embedded gets through the kernel driver to activate graphic function. 14

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Cloud computing here can perform rapid fingerprint identification and facial recognition in order to fulfill the access control system [21]. 15

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C. Implementing VVoIP at Hadoop with web interface (1) According to an open source IHU (a voice over IP application program), we have established a video/voice over IP application on Linux system to develop VVoIP over two PCs as shown in Fig. 6 16

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(2) Activating a database in a cloud computing server to record the necessary information like account, IP address and so on. (3) Constructing the web services in order to connect a database in Hadoop cloud computing server for implementing the VVoIP applications, user account and login, as shown in Figs. 7 and 8. (4) Transplanting the video/voice over IP application into cloud computing server incorporation with web interface and database. 17

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D. Intelligent adaptation for VVoIP on cloud computing In terms of quality of services (QoS) implemented in the video phone call over IP, we have to tackle some of crucial problems about jitter, loss, latency, and throughput so as to maintain the smooth video/voice streaming over internet. 19

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EMPIRICAL RESULTS AND DISCUSSIONS 20

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CONCLUSIONS In this study we have moved the VVoIP applications from user devices to Hadoop cloud computing system with access control to implement rapid facial/fingerprint identifications. User does not need to use a real IP and have a friendly web interface. This scheme reduces computation load and power consumption dramatically at user devices In addition, we employed a BPNN to tune parameters appropriately for adapting seamless handoff and analyzing network traffic over time. 25