ABSTRACT

Traditional routing metrics designed for wireless networks are application-agnostic. In this paper, we consider a wireless network where the application flows consist of video traffic. From a user perspective, reducing the level of video distortion is critical. We ask the question “Should the routing policies change if the end-to-end video distortion is to be minimized?” Popular link-quality-based routing metrics (such as ETX) do not account for dependence (in terms of congestion) across the links of a path; as a result, they can cause video flows to converge onto a few paths and, thus, cause high video distortion. To account for the evolution of the video frame loss process, we construct an analytical framework to, first, understand and, second, assess the impact of the wireless network on video distortion. The framework allows us to formulate a routing policy for minimizing distortion, based on which we design a protocol for routing video traffic. We find via simulations and testbed experiments that our protocol is efficient in reducing video distortion and minimizing the user experience degradation.

SYSTEM ANALYSIS

EXISTING SYSTEM:

• Different approaches exist in handling such an encoding and transmission. The Multiple Description Coding (MDC) technique fragments the initial video clip into a number of sub-streams called descriptions.
• Standards like the MPEG-4 and the H.264/AVC provide guidelines on how a video clip should be encoded for a transmission over a communication system based on layered coding. Typically, the initial video clip is separated into a sequence of frames of different importance with respect to quality and, hence, different levels of encoding.
• In another existing model, an analytical framework is developed to model the effects of wireless channel fading on video distortion.
• In other existing model, the authors examine the effects of packet-loss patterns and specifically the length of error bursts on the distortion of compressed video.

DISADVANTAGES OF EXISTING SYSTEM:

• From a user perspective, maintaining a good quality of the transferred video is critical.
• The video quality is affected by: 1) the distortion due to compression at the source, and 2) the distortion due to both wireless channel induced errors and interference.
• The model is, however, only valid for single-hop communication.
• The existing model is used not only for performance evaluation, but also as a guide for deploying video streaming services with end-to-end quality-of-service (QoS) provisioning.

PROPOSED SYSTEM:

• In this paper, our thesis is that the user-perceived video quality can be significantly improved by accounting for application requirements, and specifically the video distortion experienced by a flow, end-to-end. Typically, the schemes used to encode a video clip can accommodate a certain number of packet losses per frame. However, if the number of lost packets in a frame exceeds a certain threshold, the frame cannot be decoded correctly.
• A frame loss will result in some amount of distortion. The value of distortion at a hop along the path from the source to the destination depends on the positions of the unrecoverable video frames (simply referred to as frames) in the GOP, at that hop.
• As one of our main contributions, we construct an analytical model to characterize the dynamic behavior of the process that describes the evolution of frame losses in the GOP (instead of just focusing on a network quality metric such as the packet-loss probability) as video is delivered on an end-to-end path.
• Specifically, with our model, we capture how the choice of path for an end-to-end flow affects the performance of a flow in terms of video distortion. Our model is built based on a multilayer approach.

ADVANTAGES OF PROPOSED SYSTEM:

• Our solution to the problem is based on a dynamic programming approach that effectively captures the evolution of the frame-loss process.
• Minimize routing distortion.
• Since the loss of the longer I-frames that carry fine-grained information affects the distortion metric more, our approach ensures that these frames are carried on the paths that experience the least congestion; the latter frames in a GOP are sent out on relatively more congested paths.
• Our routing scheme is optimized for transferring video clips on wireless networks with minimum video distortion.
  
  
• SYSTEM REQUIREMENTS
• SOFTWARE REQUIREMENTS:
• •             Web Technologies                                           :               HTML, CSS, JS. JSP
• •             Programming Language                                 :               Java
• •             Database Connectivity                                   :               JDBC
• •             Backend Database                                          :               MySQL
• •             Operating System                                           :               Windows 08/10
• HARDWARE REQUIREMENTS:
• •             Pentium processor                          :               Core I3
• •             RAM Capacity                                 :               2 GB
• •             Hard Disk                                        :               250GB
• •             Monitor                                                               :               15’’ Color Monitor