Mobile Multimedia Communications. 7th International ICST Conference, MOBIMEDIA 2011, Cagliari, Italy, September 5-7, 2011, Revised Selected Papers

Research Article

Multi-stream Rate Adaptation Using Scalable Video Coding with Medium Grain Scalability

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  • @INPROCEEDINGS{10.1007/978-3-642-30419-4_14,
        author={Sergio Cical\'{o} and Abdul Haseeb and Velio Tralli},
        title={Multi-stream Rate Adaptation Using Scalable Video Coding with Medium Grain Scalability},
        proceedings={Mobile Multimedia Communications. 7th International ICST Conference, MOBIMEDIA 2011, Cagliari, Italy, September 5-7, 2011, Revised Selected Papers},
        proceedings_a={MOBIMEDIA},
        year={2012},
        month={5},
        keywords={SVC MGS rate-distortion modeling rate adaptation quality fairness},
        doi={10.1007/978-3-642-30419-4_14}
    }
    
  • Sergio Cicalò
    Abdul Haseeb
    Velio Tralli
    Year: 2012
    Multi-stream Rate Adaptation Using Scalable Video Coding with Medium Grain Scalability
    MOBIMEDIA
    Springer
    DOI: 10.1007/978-3-642-30419-4_14
Sergio Cicalò1,*, Abdul Haseeb1,*, Velio Tralli1,*
  • 1: University of Ferrara (ENDIF)
*Contact email: sergio.cicalo@unife.it, abdul.haseeb@unife.it, velio.tralli@unife.it

Abstract

Multiple video streaming in a shared channel with constant bandwidth requires rate adaptation in order to optimize the overall quality. In this paper we propose a multi-stream rate adaptation framework with reference to the scalable video coding (SVC) extension of the H.264/AVC standard with medium grain scalability (MGS) and quality layer (QL). We first provide a general discrete multi-objective problem formulation with the aim to maximize the sum of assigned rates while minimizing the differences among distortions under a total bit-rate constraint. A single-objective problem formulation is then derived by applying a continuous relaxation to the problem. We also propose a simplified continuous semi-analytical model that accurately estimates the rate-distortion relationship and allows us to derive an optimal and low-complexity procedure to solve the relaxed problem. The numerical results show the goodness of our framework in terms of error gap between the relaxed and its related discrete solutions, the significant performance improvement with respect to an equal-rate adaptation scheme, and the lower complexity with respect to a sub-optimal algorithm proposed in the literature.