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Real time video streaming platform device for mobile networks

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Objective:

  • In this paper, to realized a prototype of this architecture to validate the feasibility of the proposed method.
  • According to the experiment, this method could provide efficient self-adaptive multimedia streaming services for varying bandwidth environments.

 

 Domain: Cloud Computing

 

Synopsis:

Cloud multimedia services provide a capable, flexible, and scalable data processing method and offer a elucidation for the user demands of high quality and diversify multimedia. Generally speaking, accessing multimedia video services through networks is no longer a problem.

The major video platforms, such as YouTube and Amazon, have good management styles and provide users to share multimedia videos easily with diversified services. No matter what the service is, users will always expect powerful, sound and stable functions. For multimedia videos, stability is of the greatest importance. As intelligent mobile phones and wireless networks become more and more popular, network services for users are no longer limited to the home.

Multimedia information can be obtained easily using mobile devices; allowing users to enjoy everywhere network services. Considering the limited bandwidth available for mobile streaming and different device desires, this study presented a network and device-aware Quality of Service (QoS) approach that provides multimedia data suitable for a workstation unit environment via interactive mobile streaming services, further considering the overall network environment and adjusting the interactive transmission frequency and the dynamic multimedia trans coding, to avoid the waste of bandwidth and terminal power. Finally, this study realized a prototype of this architecture to validate the probability of the proposed method. According to the experiment, this method could provide efficient self-adaptive multimedia streaming services for varying bandwidth environments.

 

Existing System:

Dynamic Adaptive Streaming over HTTP (DASH) is a recent MPEG standard for IP video delivered. However, it does not impose any adaptation logic for selecting the quality of the media segments requested by the client, which is crucial to cope effectively with bandwidth fluctuations, notably in wireless channels.

Existing system compute control policies online by learning from experience, algorithm solves the control problem offline, leading promptly to better results. In addition, to compared algorithm to others during a streaming simulation.

 

 Limitations:

  • Video communication over mobile broadband networks today is challenging due to limitations in bandwidth and difficulties in maintaining high reliability, quality, and latency demands imposed by rich multimedia applications.
  • Increasing in network traffic by the use of multimedia content and applications.
  • The video quality version can only be manually selected by users and such decision can be error-prone.

 

Proposed System:

  • The proposed system provided an efficient interactive streaming service for diversified mobile devices and dynamic network environments.
  • When a mobile device requests a multimedia streaming service, it transmits its hardware and network environment parameters to the profile agent in the cloud environment, which records the mobile device codes and determines the required parameters.
  • Then transmits them to the Qos Management (QosM). The QosM determines the most suitable SVC code for the device according to the parameters, and then the SVC Transcoding Controller (STC) hands over the Trans coding work via map-reduce to the cloud, in order to increase the Trans coding rate.
  • The multimedia video file is transmitted to the mobile device through the service.

 

 Advantages:

  • The network bandwidth can be changed dynamically.
  • This method could provide efficient self-adaptive multimedia streaming services.

 

System Architecture:

Real time video streaming platform device for mobile networks

 

 

Hardware And Software Specification:

Hardware:

  • 1 GB RAM
  • 80 GB Hard Disk
  • Intel Processor
  • Android Phone with 3G Net Connection
  • Data Card
  • Net Connection

 

 Software :

  • Windows OS
  • JDK 1.7
  • Eclipse with Android
  • Glassfish Server
  • NetBeans IDE
  • MySql Server
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  • Price
    Free
  • Instructor pantech team
  • Duration 15 Hrs
  • Enrolled 0 student
  • Access 3 Months

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