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donkeyswarmMobile - Wireless

Nov 24, 2013 (3 years and 9 months ago)

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Energy
-
Efficient Cooperative Video Distribution with
Statistical QoS Provisions over Wireless Networks




ABSTRACT:


For real
-
time video broadcast where multiple users are interested in the same
content, mobile
-
to
-
mobile cooperation can

be utilized to
improve delivery
efficiency and reduce network utilization. Under such cooperation, however, real
-
time video

transmission requires end
-
to
-
end delay bounds. Due to the inherently
stochastic nature of wireless fading channels, deterministic delay

bounds are
prohibitively difficult to guarantee. For a scalable video structure, an alternative is
to provide statistical guarantees using

the concept of effective capacity/bandwidth
by deriving quality of service exponents for each video layer. Using this concept,
w
e

formulate the resource allocation problem for general multi
-
hop multicast
network flows and derive the optimal solution that minimizes

the total energy
consumption while guaranteeing a statistical end
-
to
-
end delay bound on each
network path. A method is
described to

compute the optimal resource allocation at
each node in a distributed fashion. Furthermore, we propose low complexity
approximation

algorithms for energy
-
efficient flow selection from the set of
directed acyclic graphs forming the candidate ne
twork flows. The flow

selection
and resource allocation process is adapted for each video frame according to the
channel conditions on the network links.

Considering different network topologies,
results demonstrate that the proposed resource allocation an
d flow selection
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algorithms

provide notable performance gains with small optimality gaps at a low
computational cost.


SYSTEM ARCHITECTURE:



EXISTING SYSTEM:


THE real
-
time nature of video broadcast demands quality
-
of
-
service (QoS)
guarantees such as
delay bounds for

end
-
user satisfaction. Given the bit rate
requirements of

such services, delivery efficiency is another key objective.
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Deterministic delay bounds are prohibitively expensive

to guarantee over wireless
networks. Consequently, to

provide a r
ealistic and accurate model for quality of
service,

statistical guarantees are considered as a design guideline

by defining
constraints in terms of the delay
-
bound violation probability. The notion of
statistical QoS is tied

back to the well
-
developed theo
ry of effective bandwidth and
its dual concept of effective capacity


DISADVANTAGES OF EXISTING SYSTEM:


For general multihop multicast

network scenarios, it is inefficient to allocate
resources

independently among network links since the variation in

the
supported
service rates among different links affects the

end
-
to
-
end transport capability in the
network.



PROPOSED SYSTEM:


Cooperation among mobile devices in wireless networks

has the potential to
provide notable performance gains in

terms of increasin
g the network throughput,
extending the network coverage, decreasing the end
-
user communication cost,
decreasing the energy consumption. In this work, we develop optimized flow
selection and

resource allocation schemes that can provide end
-
to
-
end

statistic
al
delay bounds and minimize energy consumption

for video distribution over
cooperative wireless networks.

The network flow for video content distribution can
be any

sequential multihop multicast tree forming a directed

acyclic graph that
spans the network

topology. We model

the queuing behavior of the cooperative
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network according

to the effective capacity link layer model. Based on this

model,
we formulate and solve the flow resource allocation

problem to minimize the total
energy consumption subject

to e
nd
-
to
-
end delay bounds on each network path.
Moreover,

we propose two approximation algorithms to solve

the flow selection
problem which involves selecting the

optimal flow in terms of minimizing energy
consumption.



ADVNATAGES OF PROPOSED SYSTEM:


The
advantages of cooperation among mobile devices in

wireless networks have
been also revealed for video

streaming applications


MODULES:



Cooperative network model



Queuing network model for multihop layered Video transmission



Effective bandwidth/capacity
model



Energy
-
efficient resource allocation and Flow selection



Combinatorial encoding of network flows


MODULES DESCRIPTION:

Cooperative network model

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The proposed system model consists of a base station (BS),

denoted by M0, and K
MSs M1; . . .;MK which are

capable

of transmitting, receiving, or relaying a
scalable video

bitstream. The BS is responsible for distributing the same

multilayer
video stream to the MSs over wireless fading

channels. We define a flow as a tree
of adjacent links that

represents
consecutive unicast/multicast transmissions. We

are given a set of N candidate flows where the nth flow is

defined by a set of links
Fn which form a directed acyclic

tree (DAG)


Queuing network model for multihop layered Video transmission

A separate queue

is maintained for each video layer at each

node. The arrival
process at the BS is denoted fA0;lgL

l¼1 and

is determined by the scalable codec
parameters and the

video content. The behavior of the queue
-
length process in
queuing

based

communication network
s is extensively treated.


Effective bandwidth/capacity model

The effective capacity channel model captures a generalized

link
-
level capacity
notion of the fading channel by

characterizing wireless channels in terms of
functions that

can be easily mapped t
o link
-
level QoS metrics, such as

delay
-
bound
violation probability. Thus, it is a convenient

tool for designing QoS provisioning
mechanisms


Energy
-
efficient resource allocation and Flow selection

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In this section, we formulate and solve the problem of

hyb
rid unicast/multicast
resource allocation over multihop

cooperative networks with statistical end
-
to
-
end
delay

bounds. Moreover, we present a procedure for time slot

adaptation and flow
selection over the multihop links to

obtain the optimal solution.


Combinatorial encoding of network flows


Furthermore, Prufer devised a method for encoding and

decoding the set of
spanning trees in a graph using what is

known as Prufer sequences. The Prufer

decoding algorithm provides the inverse function, that is,

give
n a Prufer sequence
of K _ 1 elements, we can find the

set of edges that construct the unique spanning
tree

corresponding to the Prufer sequence. This provides a

handy tool for
implementing the brute force approach

combinatorially to obtain insight into th
e
optimal flow

selection and analyze the performance of other approximation

algorithms.


HARDWARE REQUIREMENTS



Processor


: Any Processor above 500 MHz.



Ram



: 128Mb.



Hard Disk


: 10 GB.



Compact Disk


: 650 Mb.



Input device


: Standard Keyboard and Mouse.

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Output device


: VGA and High Resolution Monitor


SOFTWARE REQUIREMENTS



Operating System

: Windows XP.



Coding Language


:
JAVA


REFERENCE:

Amin Abdel Khalek, and Zaher Dawy, “Energy
-
Efficient Cooperative Video

Distribution with Statistical QoS

Provisions over Wireless Networks”,
IEEE
TRANSACTIONS ON MOBILE COMPUTING, VOL. 11, NO. 7, JULY 2012
.