tnijv1 a real-time adaptive algorithm for video
DESCRIPTION
Various supports: Base paper, Abstract, All review presentation (Including UML diagrams) Lab Practice (min 10 to 15 classes) final document (including-- video output, screen shorts) With Regards...* *Ranjith kumaR. K* TRIPLE N INFOTECH 73/5,3rd FLOOR,SRI KAMATCHI COMPLEX OPP.CITY HOSPITAL (NEAR LAKSHMI COMPLEX) SALAI ROAD,Trichy - 620 018, Ph: 0431 4050403, 7200021403, 7200021404.TRANSCRIPT
A Real-Time Adaptive Algorithm for Video Streaming over
Multiple Wireless Access Networks
OBJECTIVE
In this paper, we 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.
Abstract:
In this work we have a present the characterization of the mobile network traffic generated by
one of the foremost relevant social networking applications: YouTube. Understanding its
characteristics is of major importance to evaluate its impact on mobile networks and optimize
network or application style. Video streaming is gaining quality among mobile users. the
foremost recent mobile devices, like sensible phones and tablets, unit equipped with multiple
wireless network interfaces. How to with efficiency and cost-effectively utilize multiple links to
improve video streaming quality wishes investigation. so as to maintain high video streaming
quality whereas reducing the wireless service value, throughout this paper, the optimum video
streaming technique with multiple links is developed as a Markov call technique (MDP). The
reward operate is supposed to think over the standard of service (QoS) desires for video traffic,
rather like the startup latency, playback fluency, average playback quality, playback smoothness
and wireless service value. to resolve the MDP in real time, we've a bent to propose associate
adaptive , best-action search rule to obtain a sub-optimal answer. to guage the performance of
the planned adaptation rule, we've a bent to implemented a testbed using the automaton itinerant
and collectively the climbable Video writing (SVC) codec. Additionally, the mobile terminal can
strongly influence the download. Our results with high-end Android terminals show that the
client implements a dual-threshold buffer policy that interrupts and resumes the download
depending on its buffer occupancy.
EXISTING SYSTEM
In the previous service, the mobile device side exchanges information with the cloud
environment, so as to determine an optimum multimedia video. Scholars have done numerous
researches toward conventional platform (CDN) to store different movie formats in a multimedia
server, to choose the right video stream according to the current network situation or the
hardware calculation capabilities. To solve this problem, many researchers have attempted
dynamic encoding to transfer media content, but still cannot offer the best video quality.
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.
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.
The most suitable SVC code for the device according to the parameters, and then the
SVC Transcoding Controller (STC) hands over the transcoding work via map-reduce to
the cloud, in order to increase the transcoding 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.
Block diagram:
HARDWARE AND SOFTWARE SPECIFICATION:
Software Requirement:
1. Language - Java (JDK 1.7)
2. OS - Windows
3. Build Tool - Mobile
4.Netbeans ide 7.1.2
5.Android develop tool
Hardware Requirement:
1. 1 GB RAM
2. 80 GB Hard Disk
3. Intel Processor