A dynamic congestion avoidance in Multipath Routing for Video Traffic In Wireless

multihop Networks

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 test bed experiments that our protocol is efficient in reducing

video distortion and minimizing the user experience degradation.

AIM

The aims of this paper are an analytical framework to, first, understand and, second, assess the

impact of the wireless network on video transmission distortion.

SCOPE

The Scope of this paper is allows us to formulate a routing policy for minimizing intruder

detection , based on which we design a protocol for routing video traffic.

EXISTING SYSTEM

In these protocols, one of the critical functionalities that is often neglected, but affects the end-to-

end quality of a video flow, is routing. Typical routing protocols, designed for wireless multi hop

settings, are application-agnostic and do not account for correlation of losses on the links that

compose a route from a source to a destination node. Furthermore, since flows are considered

independently, they can converge onto certain links that then become heavily loaded (thereby

increasing video distortion), while others are significantly underutilized. The decisions made by

such routing protocols are based on only network (and not application) parameters. 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. The packet-loss probability on a

link is mapped to the probability of a frame loss in the GOP. The frame-loss probability is then

directly associated with the video distortion metric.

DISADVANTAGES:

From a user perspective, reducing the level of video distortion is critical.

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.

 PROPOSED SYSTEM

In this paper, Developing an analytical framework to capture the impact of routing on video

distortion: As our primary contribution, we develop an analytical framework that captures the

impact of routing on the end-to-end video quality in terms of distortion Design of a practical

routing protocol for distortion-resilient video delivery: Based on our analysis, we design a

practical routing protocol for a network that primarily carries wireless video Evaluations via

extensive experiments: We demonstrate via extensive simulations and real test bed experiments

on a multi hop 802.11a test bed that our protocol is extremely effective in reducing the end-to-

end video distortion and keeping the user experience degradation to a minimum

One approach especially applicable to flat WSNs is for an intermediate node to feedback

maliciousness and energy status of its neighbor nodes to the sender node (e.g., the source or sink

node) who can then utilize the knowledge to route packets to avoid nodes with unacceptable

maliciousness or energy status. Another approach which we adopt in this paper is to use local

host-based IDS for energy conservation.

the cost of executing the dynamic algorithm described above, including periodic clustering,

periodic intrusion detection, and query processing through multipath routing, in terms of energy

consumption.

ADVANTAGES

Our simulation study shows that the distortion (in terms of PSNR) is decreased by 20%

compared to ETX-based routing

The user experience degradation due to increased traffic load in the network is kept to a

minimum.

Algorithm 1:

Path discovery (Uses Algorithm 2)

Input: source node , destination node

Input: frame size

Output: route from to

1: /* DSR Route Discovery Phase */

2: send

3: receive messages

4: N node-ids from messages

5:

6: /*Path Discovery Initialization Phase*/

B

10:

11:

12: append to

13:

14: /* Path Computation /*

15: repeat

16: Next_node_in_optimal path( B N )

:

The value of the distortion at hop along the path from the source to the destination node depends

on the position of the first unrecoverable frame in the GOP. We define the process such that is

the index of the first unrecoverable frame in the GOP structure at hop . At each hop , the process

takes values in the set

Modules :

1. Constructing Sensor Network

In this module, we are going to connect the network .Each network is connected the neighboring

network and it is independently deployed in network area. And also deploy the each ip address is

authorized in a network.

2.Video Input Module:

The Input Module is designed as such a way that the proposed system must be capable of

handling any type of data formats, such as if the user wishes to hide any image format then it

must be compatible with all usual image formats such as jpg, gif, bmp, it must be also

compatible with video formats such as .avi, .flv, . etc.. And also it must be compatible with

various document formats, video quality is affected by: 1) the distortion due to compression at

the source, and 2) the distortion due to both wireless channel intruder induced errors and

interference

2.1 Video Transmission:

The path selection browses and selects the source file. And selected video data is

converted into fixed size of packets. And the video is send from source to destination,

maintenance and data transmission is consecutive process which happens in split seconds

in real-time transmission. Hence the paths allocated priory is used for videos

transmission. The first path allocated previously is now used for data transmission. The

data is transferred through the highlighted path. The second path selected is now used for

data transmission. The data is transferred through the highlighted path. The third path

selected is used for video transmission. The video data is transferred through the

highlighted path. browse and select the source file. And selected video data is converted

into fixed size of packets. And the video is send from source to destination.

3. Multi path Routing

Multihop routing is considered an effective mechanism for fault and intrusion tolerance

to improve video data delivery in WSNs. The basic idea is that the probability of atleast one path

reaching the sink node or base station increases as we have more paths doing data delivery.

While most prior research we focused on using multipath routing to improve reliability, of video

traffic some attention has been paid to using multipath routing to tolerate insider delay attacks

4. Video Distortion Filtering method:

The video distortations defined as a mechanism for a WSN to detect the existence of

inappropriate, incorrect, or anomalous moving video . In this module check whether the path is

authorized or unauthorized. If path is authorized the video packet is send to valid destination.

Otherwise the video will be filtered deleted. According ip address only we are going to find the

path is authorized or Unauthorized. If the video packet is received from other than the port no it will

be filtered and discarded. This filter only removes the unauthorized video packets and authorized video

packets send to destination.

Simulation Process

In this module, we will show the cost of executing the Path discovery algorithm

described above, including periodic video traffic, periodic videos detection, and query processing

through multipath routing, in terms of energy consumption will displayed in graph method..

SYSTEM CONFIGURATION:-

HARDWARE REQUIREMENTS:

Processor             –   Pentium –IV

Speed                   –   1.1 Ghz

RAM                  –   512 MB(min)

Hard Disk          –   40 GB

Key Board         –   Standard Windows Keyboard

Mouse                –  Two or Three Button Mouse

Monitor              –  LCD/LED

SOFTWARE REQUIREMENTS:

Operating System : Windows 7

Front End          : .NET

Database          : SQLSERVER 2008

Tool                  : VB2010