SMART PRO TECHNOLOGIES
9885652333, www.smartprotech.net
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, realtime 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
SMART PRO TECHNOLOGIES
9885652333, www.smartprotech.net
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
SMART PRO TECHNOLOGIES
9885652333, www.smartprotech.net
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
SMART PRO TECHNOLOGIES
9885652333, www.smartprotech.net
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:
SMART PRO TECHNOLOGIES
9885652333, www.smartprotech.net
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
SMART PRO TECHNOLOGIES
9885652333, www.smartprotech.net
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.
SMART PRO TECHNOLOGIES
9885652333, www.smartprotech.net
 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.