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,
we 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 network 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 and flow
selection 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. Deterministic delay bounds are
prohibitively expensive to guarantee over wireless networks. Consequently, to provide
a realistic 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 theory 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 increasing 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 statistical 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 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 end-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
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 networks 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 to 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
In this section, we formulate and solve
the problem of hybrid 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, given 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 the 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.
·
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.
