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Energy-Efficient Cooperative Video Distribution with Statistical QoS Provisions over Wireless Networks – projects 2012

projects 2012

Energy-Efficient Cooperative Video Distribution with Statistical QoS Provisions over Wireless Networks – projects 2012

Abstract:Energy-Efficient Cooperative Video Distribution with Statistical QoS Provisions over Wireless Networks- projects 2012

Technology Used: Java

AIM

Minimizing energy consumption in battery-operated mobile devices is essential for the development of next generation heterogeneous wireless communications systems. In this work, we develop optimized flow selection and resource allocation schemes that can provide end-to-end statistical delay bounds and minimized energy consumption for video distribution over cooperative 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 multihop 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.

SCOPE OF WORK

Minimizing energy consumption in battery-operated mobile devices is essential for the development of next generation heterogeneous wireless communications systems. Enhancement schemes and communication architectures with cooperation among mobile devices to reduce energy consumption appear extensively in the literature. A cooperative network architecture is presented and experimentally evaluated to reduce energy consumption in multi-radio mobile devices for video streaming applications. A comprehensive experimental study is conducted where results presented demonstrate notable energy reduction gains by collaborative downloading. The problem of resource allocation with statistical QoS guarantees and optimized energy consumption over cooperative networks with general topologies has not been tackled yet in the literature. Optimized rate allocation and routing over cooperative wireless networks is also studied, it is fundamentally different from the proposed work since it considers minimizing energy consumption in mobile terminals as the central objective, providing statistical delay guarantees, and capturing layered video content with QoS requirements per layer.

OBJECTIVES

To develop optimized flow selection and resource allocation schemes that can provide end-to-end statistical delay bounds and minimized 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. It is modeled the queuing behavior of the cooperative network according to the effective capacity link layer model. Based on this model, the flow resource allocation problem has been solved to minimize the total energy consumption subject to end-to-end delay bounds on each network path. Two approximation algorithms to solve the flow selection problem which involves selecting the optimal flow in terms of minimizing energy consumption.

PROBLEM STATEMENT

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. For scalable video transmission, a set of QoS exponents for each video layer are obtained by applying the effective bandwidth/capacity analyses on the incoming video stream to characterize the delay requirement. 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. 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, and decreasing the energy consumption. A near-optimal solution is shown to reduce end-user cost while meeting distortion and delay constraints.

PROBLEM SOLUTION

Two approximation algorithms to solve the flow selection problem, which involves selecting the optimal flow in terms of minimizing energy consumption. The first algorithm uses negated signal-to-noise ratios as link weights on the complete network graph, finds the minimum spanning tree using those weights to maximize the sum rate, and performs optimal resource allocation on the flow corresponding to the obtained tree structure. The second algorithm maintains a set of dominant flows that are optimal for a potentially large percentage of channel states under a certain network topology and performs flow selection on that dominant set. By updating the optimal allocation and flow selection iteratively in each time frame according to the instantaneous channel states, we effectively reselect the best network flow and reconfigure the service process on each link to provide optimized end-to-end transport.

INTRODUCTION

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. The H.264/AVC video coding standard is designed to provide high coding efficiency that is suitable for wireless video transmission. To provide a network-friendly design, the scalable video coding (SVC) extension of H.264 allows rate scalability at the bitstream level by generating embedded bit-streams that are partially decodable at different bitrates with degrading quality. The basic level of quality is supported by the base layer and incremental improvements are provided by the enhancement layers. Video source rate scalability can be achieved with temporal, spatial, or quality scalability.

ASSUMPTIONS MADE

Mobile Stations (MSs) are assumed to be connected to several wireless networks with different characteristics in terms of bandwidth, packet loss probability, and transmission cost. Signal to Nose Ratio (SNR) for mobile nodes has been generated using random number function.

EXISTING 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 and decreasing the energy consumption. For example, the ICAM architecture presents an integrated cellular and ad hoc multicast scheme to increase the cellular multicast throughput through the use of mobile stations (MSs) as ad hoc relays. In the UCAN architecture, the MSs use their WLAN interface to enhance the throughput and increase the coverage of a wireless wide area network. MSs are assumed to be connected to several wireless networks with different characteristics in terms of bandwidth, packet loss probability, and transmission cost.

The advantages of cooperation among mobile devices in wireless networks have been also revealed for video streaming applications. For example, the CHUM architecture assumes that all mobile devices are interested in the same video content that is divided into multiple descriptions; each mobile device randomly selects and pulls a video description through a cellular link and multicasts it to all members in its cooperation group which is formed in an ad-hoc manner.

Disadvantages

  • 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.
  • Considered only optimized rate allocation and routing over cooperative wireless networks,


PROPOSED SYSTEM

To develop optimized flow selection and resource allocation schemes that can provide end-to-end statistical delay bounds and minimized 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.

Model the queuing behavior of the cooperative network according to the effective capacity link layer model. Based on this model, 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.

To propose two approximation algorithms to solve the flow selection problem which involves selecting the optimal flow in terms of minimizing energy consumption. The first algorithm uses negated signal-to-noise ratios as link weights on the complete network graph, finds the minimum spanning tree using those weights to maximize the sum rate, and performs optimal resource allocation on the flow corresponding to the obtained tree structure. The second algorithm maintains a set of dominant flows that are optimal for a potentially large percentage of channel states under a certain network topology and performs flow selection on that dominant set. By updating the optimal allocation and flow selection iteratively in each time frame according to the instantaneous channel states, we effectively reselect the best network flow and reconfigure the service process on each link to provide optimized end-to-end transport.

Advantages

  • Minimized energy consumption
  • Optimized flow selection and resource allocation
  • Video distribution over cooperative wireless networks

Posted by on Jun 30th, 2012 and filed under DEMO, Mobile Computing. You can follow any responses to this entry through the RSS 2.0. You can leave a response by filling following comment form or trackback to this entry from your site

5 Responses for “Energy-Efficient Cooperative Video Distribution with Statistical QoS Provisions over Wireless Networks – projects 2012”

  1. Girish says:

    Sir i need this project can u plz tell hw it works and wt the cost of this project….

  2. leelarani says:

    i want code for this project and how energy will efficient in this please reply me

  3. raju says:

    please send the abstract of
    SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emergency.

  4. akshata.r says:

    plz send some information on existing system and drawbacks of existing system n proposed sytem. and the algorithm used in energy efficient cooperative vedio distribution with stastistical qos provisions over wireless networks

  5. santosh says:

    i want code for this project and how energy will efficient in this project please reply me

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