A Real-Time Adaptive Algorithm for Video
Streaming over Multiple Wireless Access Networks
ABSTRACT:
Video streaming
is gaining popularity among mobile users. The latest mobile devices, such as
smart phones and tablets, are equipped with multiple wireless network
interfaces. How to efficiently and cost-effectively utilize multiple links to
improve video streaming quality needs investigation. In order to maintain high
video streaming quality while reducing the wireless service cost, in this
paper, the optimal video streaming process with multiple links is formulated as
a Markov Decision Process (MDP). The reward function is designed to consider
the quality of service (QoS) requirements for video traffic, such as the
startup latency, playback fluency, average playback quality, playback
smoothness and wireless service cost. To solve the MDP in real time, we propose
an adaptive, best-action search algorithm to obtain a sub-optimal solution. To
evaluate the performance of the proposed adaptation algorithm, we implemented a
testbed using the Android mobile phone and the Scalable Video Coding (SVC)
codec. Experiment results demonstrate the feasibility and effectiveness of the
proposed adaptation algorithm for mobile video streaming applications, which
outperforms the existing state-of-the-art adaptation algorithms
EXISTING SYSTEM:
Video streaming
is gaining popularity among mobile users recently. Considering that the mobile
devices have limited computational capacity and energy supply, and the wireless
channels are highly dynamic, it is very challenging to provide high quality
video streaming services for mobile users consistently. It is a promising trend
to use multiple wireless network interfaces with different wireless
communication techniques for mobile devices. Meanwhile, as video data are
transmitted over HTTP protocols, the video streaming service can be deployed on
any web server. However, the video quality version can only be manually
selected by users and such decision can be error-prone.
DISADVANTAGES
OF EXISTING SYSTEM:
]
The
smart phones only have limited storage space, it is impractical to maintain a
very large buffer size.
]
The
buffered unwatched video may be wasted if the user turns off the video player
or switches to other videos.
]
Download
typically does not support transmitting video data over multiple links.
PROPOSED SYSTEM:
In this paper we
proposed dynamic adaptive streaming over HTTP has been proposed. In a DASH
system, multiple copies of pre-compressed videos with different resolution and
quality are stored in segments. We formulate the multi-link video streaming
process as a reinforcement learning task. For each streaming step, we define a
state to describe the current situation, including the index of the requested
segment, the current available bandwidth and other system parameters. A
finitestate Markov Decision Process (MDP) can be modeled for this reinforcement
learning task. The reward function is carefully designed to consider the video
QoS requirements, such as the interruption rate, average playback quality, and
playback smoothness, as well as the service costs
ADVANTAGES
OF PROPOSED SYSTEM:
ü
Smooth
and high quality video streaming.
ü
Avoid
playback interruption and achieve better smoothness and quality.
SYSTEM
REQUIREMENTS:
HARDWARE REQUIREMENTS:
Ø
System : Pentium IV 2.4 GHz.
Ø
Hard Disk : 40
GB.
Ø
Floppy Drive : 1.44
Mb.
Ø
Monitor : 15 VGA Colour.
Ø
Mouse :
Logitech.
Ø Ram : 512 Mb.
Ø MOBILE : ANDROID
SOFTWARE
REQUIREMENTS:
Ø Operating system : Windows
XP/7.
Ø Coding Language : Java
1.7
Ø Tool Kit : Android
2.3 ABOVE
Ø IDE : Eclipse
REFERENCE:
Min Xing, Student Member, IEEE, Siyuan Xiang,
Member, IEEE, and Lin Cai, Senior Member, IEEE, “A Real-Time Adaptive Algorithm for Video Streaming
over Multiple Wireless Access Networks”, IEEE JOURNAL ON SELECTED AREAS IN
COMMUNICATIONS, VOL. 32, NO. 4, APRIL 2014.
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