### Abstract

We present optimal schemes for allocating bits of fine-grained scalable video sequences among multiple senders streaming to a single receiver. This allocation problem is critical in optimizing the perceived quality in peer-to-peer and distributed multi-server streaming environments. Senders in such environments are heterogeneous in their outgoing bandwidth and they hold different portions of the video stream. We formulate the allocation problem as an optimization problem, which is nonlinear in general. We use rate-distortion models in the formulation to achieve the minimum distortion in the rendered video, constrained by the outgoing bandwidth of senders, availability of video data at senders, and incoming bandwidth of receiver. We show how the adopted rate-distortion models transform the nonlinear problem to an integer linear programming (ILP) problem. We then design a simple rounding scheme that transforms the ILP problem to a linear programming (LP) one, which can be solved efficiently using common optimization techniques such as the Simplex method. We prove that our rounding scheme always produces a feasible solution, and the solution is within a negligible margin from the optimal solution. We also propose a new algorithm (FGSAssign) for the allocation problem that runs in O(n log n) steps, where n is the number of senders. We prove that FGSAssign is optimal. Because of its short running time, FGSAssign can be used in real time during the streaming session. Our experimental study validates our analytical analysis and shows the effectiveness of our allocation algorithm in improving the video quality.

Original language | English |
---|---|

Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |

Volume | 6504 |

DOIs | |

Publication status | Published - 31 Aug 2007 |

Externally published | Yes |

Event | Multimedia Computing and Networking 2007 - San Jose, CA, United States Duration: 31 Jan 2007 → 1 Feb 2007 |

### Other

Other | Multimedia Computing and Networking 2007 |
---|---|

Country | United States |

City | San Jose, CA |

Period | 31/1/07 → 1/2/07 |

### Fingerprint

### Keywords

- Distributed streaming
- FGS
- Fine-grained scalable streaming
- Peer-to-peer streaming
- Rate-distortion optimized streaming
- Video streaming

### ASJC Scopus subject areas

- Electrical and Electronic Engineering
- Condensed Matter Physics

### Cite this

*Proceedings of SPIE - The International Society for Optical Engineering*(Vol. 6504). [650402] https://doi.org/10.1117/12.706047

**Optimal bit allocation for fine-grained scalable video sequences in distributed streaming environments.** / Hsu, Chenghsin; Hefeeda, Mohamed.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of SPIE - The International Society for Optical Engineering.*vol. 6504, 650402, Multimedia Computing and Networking 2007, San Jose, CA, United States, 31/1/07. https://doi.org/10.1117/12.706047

}

TY - GEN

T1 - Optimal bit allocation for fine-grained scalable video sequences in distributed streaming environments

AU - Hsu, Chenghsin

AU - Hefeeda, Mohamed

PY - 2007/8/31

Y1 - 2007/8/31

N2 - We present optimal schemes for allocating bits of fine-grained scalable video sequences among multiple senders streaming to a single receiver. This allocation problem is critical in optimizing the perceived quality in peer-to-peer and distributed multi-server streaming environments. Senders in such environments are heterogeneous in their outgoing bandwidth and they hold different portions of the video stream. We formulate the allocation problem as an optimization problem, which is nonlinear in general. We use rate-distortion models in the formulation to achieve the minimum distortion in the rendered video, constrained by the outgoing bandwidth of senders, availability of video data at senders, and incoming bandwidth of receiver. We show how the adopted rate-distortion models transform the nonlinear problem to an integer linear programming (ILP) problem. We then design a simple rounding scheme that transforms the ILP problem to a linear programming (LP) one, which can be solved efficiently using common optimization techniques such as the Simplex method. We prove that our rounding scheme always produces a feasible solution, and the solution is within a negligible margin from the optimal solution. We also propose a new algorithm (FGSAssign) for the allocation problem that runs in O(n log n) steps, where n is the number of senders. We prove that FGSAssign is optimal. Because of its short running time, FGSAssign can be used in real time during the streaming session. Our experimental study validates our analytical analysis and shows the effectiveness of our allocation algorithm in improving the video quality.

AB - We present optimal schemes for allocating bits of fine-grained scalable video sequences among multiple senders streaming to a single receiver. This allocation problem is critical in optimizing the perceived quality in peer-to-peer and distributed multi-server streaming environments. Senders in such environments are heterogeneous in their outgoing bandwidth and they hold different portions of the video stream. We formulate the allocation problem as an optimization problem, which is nonlinear in general. We use rate-distortion models in the formulation to achieve the minimum distortion in the rendered video, constrained by the outgoing bandwidth of senders, availability of video data at senders, and incoming bandwidth of receiver. We show how the adopted rate-distortion models transform the nonlinear problem to an integer linear programming (ILP) problem. We then design a simple rounding scheme that transforms the ILP problem to a linear programming (LP) one, which can be solved efficiently using common optimization techniques such as the Simplex method. We prove that our rounding scheme always produces a feasible solution, and the solution is within a negligible margin from the optimal solution. We also propose a new algorithm (FGSAssign) for the allocation problem that runs in O(n log n) steps, where n is the number of senders. We prove that FGSAssign is optimal. Because of its short running time, FGSAssign can be used in real time during the streaming session. Our experimental study validates our analytical analysis and shows the effectiveness of our allocation algorithm in improving the video quality.

KW - Distributed streaming

KW - FGS

KW - Fine-grained scalable streaming

KW - Peer-to-peer streaming

KW - Rate-distortion optimized streaming

KW - Video streaming

UR - http://www.scopus.com/inward/record.url?scp=34548256262&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34548256262&partnerID=8YFLogxK

U2 - 10.1117/12.706047

DO - 10.1117/12.706047

M3 - Conference contribution

AN - SCOPUS:34548256262

SN - 0819466174

SN - 9780819466174

VL - 6504

BT - Proceedings of SPIE - The International Society for Optical Engineering

ER -