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Parallelizing Video Transcoding With Load Balancing On Cloud Computing
Song Lin, Xinfeng Zhang, Qin Y, Siwei Ma
Circuits and Systems, 2013 IEEE
Outline
Introduction
Related work
Problem formulation and system architecture
Proposed method
Experiment Results
Conclusion
Introduction #1
Parallel programmingShare memory
Pthread – data dependency
Message passing MPI – time delay
Introduction #2
IssuesData dependencyCost of data passingLoad balance
Introduction #3
Cloud computationData segmentationComputing capacity
Introduction #4
GOP-based encodingIndependence between GOPs
...........
Introduction #5
Paralleling in GOP-based
Thread1
Thread2
Thread3
Related work #1
FCFS - First come first server [2]Easy to implementLoad balancing problem is still exist
Related work #3
MCT – Minimal complete time [6]Map-Reduce-based
Problem formulation and system architecture #1 Load balance problem on cloud computing
Executing timeDelay time
Data passing
C is complexity and P is computing capacity
Problem formulation and system architecture #2 The overall completion time of set Sk is
.
Goal .
Problem formulation and system architecture #3 Optimal solution
.
n means n task and m means m cores
Problem formulation and system architecture #4 Flow chart of the proposed method
Problem formulation and system architecture #5For video coding, if the input sequence has
instantaneous decoder refresh (IDR) frame, this video coding task can be divided into sub-tasks.[7]
Problem formulation and system architecture #6For complexity estimation of video transcoding
tasks, the existing algorithms [8] [9] can be utilized.
Proposed method #1
The framework includes three modulesTask pre-analysisAdaptive threshold segmentationMinimal finish time
Proposed method #2
The threshold of segmentation
Proposed method #3
Proposed method #4
The optical finish time
The finish time
Proposed method #5
Assign all the tasks sequentially in descending complexity order
For each unassigned task j, the cores are judged in their descending computing capacity order according to the following criterion: assuming the task j is assigned to core k, if Τκ ≤ Tthr, the assignment is verified. Otherwise, we will judge the next core.
Proposed method #6
If all the cores are traversed and all the computing time are beyond Tthr, the task j will be assigned by MCT algorithm. and Tthr is updated to be the new finish time of the received core Tk
Proposed method #7
Experiment results #1
Experiment results #2
Experiment results #3
Conclusion
Load balancing problem is a NP-hard problem.The proposed algorithm has strong robustness to
the task launching delay.