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Exploiting Similarity for Multi-Source Downloads Using File Handprints

Reduce download time by utilizing similarity and parallelism techniques for multi-source file downloads, overcoming limitations of resource availability and network congestion. Efficient file lookup and low overhead of source locating are achieved through similarity-based handprinting.

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Exploiting Similarity for Multi-Source Downloads Using File Handprints

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  1. Exploiting Similarity for Multi-Source Downloads Using File Handprints

  2. Internet • Many files available on Internet • Many people download files from Internet • Resource is limited, long time to download files • Client bandwidth • Server capacity • Router congestion

  3. Solutions • Many files on Internet are duplicate • By use of all the available sources, client use shorter time to download files • per-file (Bit Torrent) • per-chunk (CFS and Shark) • O(N) lookup where N is no of chunks • O(1) lookup • O(1) insert mappings per file

  4. How to do? • Similarity • Lookup the similar file in O(1) • Low overhead of locating source

  5. Similarity • MP3 with different header • Movies with different language • Damage files (only few bytes of error) • Compressed file with different additional files

  6. Parallelism • Optimistic metric • Download different chunks at the same time • Client select different source for different chunks • Each source send one chunk at a time

  7. Parallelism • Conservative parallelism metric • Download one chunk at a time • Download chunk at different source

  8. Parallelism

  9. Parallelism

  10. Parallelism

  11. Handprinting Two files A and B Na no of chunks of A Nb no of chunks of B m chunks in common k selected hashes

  12. Handprinting • How many chunks (k) we selected Two files A and B Na no of chunks of A Nb no of chunks of B m chunks in common k selected hashes

  13. Implemention

  14. Evaluation

  15. Evaluation

  16. Evaluation

  17. Evaluation

  18. Evaluation

  19. Evaluation

  20. Q & A Thank You

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