5th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing

Research Article

Efficient dissemination of personalized video content in resource-constrained environments

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  • @INPROCEEDINGS{10.4108/ICST.COLLABORATECOM2009.8349 ,
        author={Piyush  Parate  and Lakshmish  Ramaswamy  and Suchendra  Bhandarkar  and Siddhartha  Chattopadhyay  and Hari  Devulapally },
        title={Efficient dissemination of personalized video content in resource-constrained environments},
        proceedings={5th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing},
        proceedings_a={COLLABORATECOM},
        year={2009},
        month={12},
        keywords={Video personalization Caching Cache replacement Request aggregation},
        doi={10.4108/ICST.COLLABORATECOM2009.8349 }
    }
    
  • Piyush Parate
    Lakshmish Ramaswamy
    Suchendra Bhandarkar
    Siddhartha Chattopadhyay
    Hari Devulapally
    Year: 2009
    Efficient dissemination of personalized video content in resource-constrained environments
    COLLABORATECOM
    ICST
    DOI: 10.4108/ICST.COLLABORATECOM2009.8349
Piyush Parate , Lakshmish Ramaswamy , Suchendra Bhandarkar , Siddhartha Chattopadhyay , Hari Devulapally

    Abstract

    Video streaming on mobile devices such as PDA's, laptop PCs, pocket PCs and cell phones is becoming increasingly popular. These mobile devices are typically constrained by their battery capacity, bandwidth, screen resolution and video decoding and rendering capabilities. Consequently, video personalization strategies are used to provide these resource-constrained mobile devices with personalized video content that is most relevant to the client's request while simultaneously satisfying the client's resource constraints. Proxy-based caching of video content is a proven strategy to reduce both client latencies and server loads. In this paper, we propose novel video personalization server and caching mechanisms, the combination of which can efficiently disseminate personalized videos to multiple resource-constrained clients. The video personalization servers use an automatic video segmentation and video indexing scheme based on semantic video content. The caching proxies implement a novel cache replacement and multi-stage client request aggregation algorithm, specifically suited for caching personalized video files generated by the personalization servers. The cache design also implements a personalized video segment calculation algorithm based on client's content preferences and resource constraints. The paper reports series of experiments that demonstrate the efficacy of the proposed techniques in scalably disseminating personalized video content to resource constrained client-devices.