stream_workflow's Introduction
Last Updated: March 13, 2018 ---------------------- About ---------------------- Prelimary workflow for streaming between a source with high throughput to an an outside computing system. Different downsampling techniques are used. A simple multicast simulation is implemented using ns2 simulator. For a quick compression analysis, compvserr.py, under Compression_analysis can be run to simulate the 3 different compression algorithms. The current raw tiffs in the directory aid in quick analysis time. New images can be place in the images directory. If the number of trials (ntrials) is set high, run -time can take 10+ minutes. ---------------------- Required to run: ---------------------- Bzip: http://www.bzip.org/ Gzip: http://www.gzip.org/ Sz: https://github.com/CODARcode/z-checker-installer GLobus*: https://www.globus.org/ Ns2 Simulator: https://www.isi.edu/nsnam/ns/ *Certain adjustments can be made to simulate streaming with globus if sandbox isn't public yet ---------------------- Files ---------------------- Downsampling |--cleared Analyzed/compressed files that have undergone blur detection and compression |--landing Place images to undergo analysis |--15522.tiff Sample data file |--README |--detectblur_tf.py Uses sz,gzip,bzip2 to compress data corresponding to flag given, removes blurry images dependent on threshold given |--exp.png Sample image file |--sz sz executable Compression_analysis |--images 1 brain image tiff sample for compression analysis |--*.raw Several raw files to enable quick results, images can be changed, results will take longer to return |--yplo1.png Current results of compression ratio comparison of sz, gzip, bzip2 |--yplo2.png Current results of compression time comparions of sz, gzip, bzip2 |--compvserr.py Runs three compression ratios on images in images folder, returns analysis in graph form Circular_Buffer |-- file_generator.py Generate random files of user-defined size |-- cache_manager.py Circular buffer management Multicast |-- multi.tcl ns-2 script for multicast simulation |-- uni.tcl ns-2 script for unicast simulation |-- throughput.awk used by the tcl scripts to compute throughput |-- analyze.py Compute average throughput and packet loss rate |-- throughput.png Result graph plotted with GNUplot ---------------------- Graphing ---------------------- To visualize compression results, go into compression_analysis and run: python compvserr.py To visualize multicast results, go to Multicast and run: python analyze.py
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