Minimum Cost Scheduling of Stored Video in Dynamic Bandwidth Allocation Networks

Reporter ： M9756003 張益瑞

IEEE Transactions on Consumer Electronics, Vol. 53, No. 2, MAY 2007

Myeong-jin Lee, Member, IEEE

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Outline

Introduction Service Cost Minimization Framework for Stored

Video Transmission Problems in Conventional Optimal Video Streaming

Algorithms Proposed Algorithm for Minimum Cost Scheduling Experimental Results Conclusion

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Introduction

Most current and future video applications will require the playback of stored video over a high-speed network.

Dynamic bandwidth allocation methods.

Renegotiated constant bit-rate (RCBR)

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Service Cost Minimization Framework for Stored Video Transmission

Dynamic Bandwidth Allocation for Video Streaming

Cost for RCBR Service of Stored Video

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Dynamic Bandwidth Allocation for Video Streaming Compressed video sources show burstiness over

multiple time-scales, periods of milliseconds to several seconds.

RCBR has the key advantage that the signaling cost and the network function for renegotiations are as simple as those of the constant bit-rate (CBR) service.

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Cost for RCBR Service of Stored Video

S=segmentR=transmission rateL=segment length

C=costS*=scheduled result

α=bandwidth cost parameterβ= renegotiation cost parameterN=the number of transmission segments in S*

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Problems in Conventional Optimal Video Streaming Algorithms Cost Functions for Transmission Segments

The Need for Minimum Cost Scheduling for Video Streaming

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Cost Functions for Transmission Segments

The transmission cost of a single isolated segment

α=bandwidth cost parameterβ= renegotiation cost parameter

the transmission cost of a group of successivesegments from Sk to Sk+n can be represented as follows.

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Cost Functions for Transmission Segments

•To show the effect of short transmission segments on the cost, the cumulative cost ratio is defined as follows.

•This represents the ratio of the transmission cost for short segments to the overall cost for the whole video sequence.

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The Need for Minimum Cost Scheduling for Video Streaming

Cumulative number of renegotiations for video streaming underRCBR service.

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The Need for Minimum Cost Scheduling for Video Streaming

Service cost for stored video under RCBR service

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Proposed Algorithm for Minimum Cost Scheduling Segment Merging as a Tool for Cost

Minimization

Relative Cost Flags for Segment Merging

Proposed Minimum Cost Scheduling Algorithm

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Segment Merging as a Tool for Cost Minimization

We define as the segment merging operator, the new ⊕segment after merging successive segments is represented by the algorithm.

The new transmission rate should be the maximum between those two segments in order to satisfy the decoder buffer underflow constraint.

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Relative Cost Flags for Segment Merging

To determine the segment merging, relative cost flags are defined for each segment. They are calculated using (7) and (8).

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Relative Cost Flags for Segment Merging

Merging of neighboring segments for minimum cost scheduling based on relative cost flags

There are three possible combinations of the left-hand and the right-hand relative cost flags.

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Relative Cost Flags for Segment Merging

Merging of neighboring segments for minimum cost scheduling based on relative cost flags

There are three cases of segment merging.1.Not merged 2.merged into the left-hand segment. 3.merged into the right-hand segment.

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Proposed Minimum Cost Scheduling Algorithm

Video traffic smoothing algorithm for the minimum service cost

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Experimental Results

Mpeg video 40,000frame GOP pattern is IBBPBBPBBPBB We assumed that renegotiation requests are

always accepted by networks.

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Experimental Results

Service cost reduction during execution of the proposedminimum cost scheduling algorithm.

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Experimental Results

Scheduled results of the proposed algorithm. Bond sequence

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Experimental Results

Overall service cost of the proposed algorithm. Bond and news sequence.

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Experimental Results

Overall service cost of the proposed algorithm. Bond and news sequence.112/04/20 22

Experimental Results

Overall service cost of the proposed algorithm. Bond and news sequence.

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Experimental Results

Characteristics of the scheduled traffic. Bond and news sequence.

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Experimental Results

Characteristics of the scheduled traffic. Bond and news sequence.

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Experimental Results

Characteristics of the scheduled traffic. Bond and news sequence.

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Conclusion A minimum cost scheduling algorithm is

proposed for high-quality video streaming in dynamic bandwidth allocation networks.

The proposed algorithm can be easily extended to other service environments with different service pricing models.

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