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An Online Video Placement Policy based on Bandwidth to Space Ratio (BSR) by Asit Dan and Dinkar Sitaram IBM T.J. Watson Research Center. Agenda. Background Aim Implementation Details Simulation Result Difficulty. Background. Video Server contain several storage devices
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An Online Video Placement Policy based on Bandwidth to Space Ratio (BSR) by Asit Dan and Dinkar Sitaram IBM T.J. Watson Research Center
Agenda • Background • Aim • Implementation Details • Simulation Result • Difficulty
Background • Video Server contain several storage devices • Each storage device has different storage and bandwidth • Each video has different popularity and it change continuously • Each video has different file size and play back bit rate • Popular movie: multiple replicas created on multiple storage devices
Aim • Balance the load • Make the best use of bandwidth and space of the storage device
Implementation Details First Phase Determines whether additional replicas are necessary (Additional expected load > free bandwidth of the devices on which the replicas reside)
Implementation Details For Example Originally movie 1’s demand is 5 unit. Device 1 contain movie 1 After some time, Movie 1’s demand change to 11 unit New replica are needed Device 1 Bandwidth: 10unit
Implementation Details Second Phase: Selection of devices BSR of the video objects on a device = Total allocated bandwidth Total allocated Space
Implementation Details For example, device 1 contain two movies, BSR of video object on device 1 = (B+C)/(E+F) bandwidth space Free D Free A Allocated for movie 1 E Allocated for movie 1 B Allocated for movie 2 F Allocated for movie 2 C
Implementation Details BSR deviation of a device: Deviation of the BSR of the video object in device from the BSR of that device BSR deviation of device 1 = |(A+B+C)/(D+E+F) – (B+C)/(E+F)|
Implementation Details For each device without this movie, • Sort device with BSR deviation in decreasing order • Place the movie in the device if BSR deviation of the device can be reduced • Loop break if additional expected load can be satisfied If the load cannot be satisfy, constraint 2 are ignore and run the loop again
Implementation Details Third Phase: Reallocate the expected load Allocate the expected load over all replicas, in order to minimize the BSR deviation of the devices
Implementation Details Bandwidth Space Bandwidth Space 2 5 8 5 Free 8 Allocated 5 5 2 Device 1 Device 2 BSR deviation of device 1 = |8/5 – 10/10| = 3/5 BSR deviation of device 2 = |2/5 – 10/10| = 3/5
Implementation Details After reallocation: Bandwidth Space Bandwidth Space 5 5 5 5 5 5 5 5 BSR deviation of device 1 = |5/5 – 10/10| = 0 BSR deviation of device 2 = |5/5 – 10/10| = 0
Implementation Details Forth Phase: Consolidation Execute only if phase 2 failed Try to decrease the replica of other movie, in order to save space and accommodate the new replicas
Implementation Details For example: place a new replica of movie 2(load : 9, space : 5) Bandwidth Space Bandwidth Space 5 1 5 1 Free 9 9 Allocated for movie 1 5 5 Device 2 Device 1
Implementation Details Bandwidth Space Bandwidth Space Free 1 5 10 1 Allocated for movie 1 9 9 5 Allocated for movie 2 Device 2 Device 1
Simulation Results • The expected load of video are in Zipf distribution • Place the video into the system • The system is unable to accommodate all video(stress test) • Test for four different configurations
Simulation Results • Each configuration contain 4 storage device • Total Bandwidth of all configurations are the same • Total Storage of all configurations are the same
Simulation Results (bandwidth,storage)
Simulation Results popularity Video index
Difficulty • Difficult to predict the expected load in the next moment accurately • Wrong Prediction has high impact on the performance of the placement policy