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8th International Conference on Mobile Multimedia Communications

Research Article

Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks

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  • @INPROCEEDINGS{10.4108/icst.mobimedia.2015.259036,
        author={Yin Wang and Jianjun Yang and Ju Shen and Bryson Payne and Juan Guo and Kun Hua},
        title={Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks},
        proceedings={8th International Conference on Mobile Multimedia Communications},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2015},
        month={8},
        keywords={camshift bandwidth balancing network traffic},
        doi={10.4108/icst.mobimedia.2015.259036}
    }
    
  • Yin Wang
    Jianjun Yang
    Ju Shen
    Bryson Payne
    Juan Guo
    Kun Hua
    Year: 2015
    Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks
    MOBIMEDIA
    ICST
    DOI: 10.4108/icst.mobimedia.2015.259036
Yin Wang1,*, Jianjun Yang2, Ju Shen3, Bryson Payne2, Juan Guo2, Kun Hua4
  • 1: Southwest Petroleum University
  • 2: University of North Georgia
  • 3: University of Dayton
  • 4: Lawrence Technological University
*Contact email: ywang12@ltu.edu

Abstract

There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs) have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select the node for the next hop with the highest potential bandwidth capacity to resume communication. Key to this strategy is that each node merely maintains two parameters that contain its historical bandwidth varying trend and then predict its near future bandwidth capacity. Then, the forwarding node selects the next hop with the highest potential bandwidth capacity. Simulations demonstrate that our approach significantly increases the data received by the sink node and decreases the delay on video transmission in Wireless Multimedia Sensor Network environments.

Keywords
camshift, bandwidth balancing, network traffic
Published
2015-08-03
Publisher
EAI
http://dx.doi.org/10.4108/icst.mobimedia.2015.259036
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