Efficient parallelized network coding for P2P file sharing applications

Karam Park, Joon Sang Park, Won Woo Ro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, we investigate parallel implementation techniques for network coding to enhance the performance of Peer-to-Peer (P2P) file sharing applications. It is known that network coding mitigates peer/piece selection problems in P2P file sharing systems; however, due to the decoding complexity of network coding, there have been concerns about adoption of network coding in P2P file sharing systems and to improve the decoding speed the exploitation of parallelism has been proposed previously. In this paper, we argue that naive parallelization strategies of network coding may result in unbalanced workload distribution and thus limiting performance improvements. We further argue that higher performance enhancement can be achieved through load balancing in parallelized network coding and propose new parallelization techniques for network coding. Our experiments show that, on a quad-core processor system, proposed algorithms exhibit up to 30% of speed-up compared to an existing approach using 1 Mbytes data with 2048×2048 coefficient matrix size.

Original languageEnglish
Title of host publicationAdvances in Grid and Pervasive Computing - 4th International Conference, GPC 2009, Proceedings
Pages353-363
Number of pages11
DOIs
Publication statusPublished - 2009 Jul 15
Event4th International Conference on Grid and Pervasive Computing, GPC 2009 - Geneva, Switzerland
Duration: 2009 May 42009 May 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5529
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th International Conference on Grid and Pervasive Computing, GPC 2009
CountrySwitzerland
CityGeneva
Period09/5/409/5/8

Fingerprint

Network coding
Network Coding
Sharing
Parallelization
Decoding
Peer-to-peer (P2P)
Parallel Implementation
Load Balancing
Exploitation
Resource allocation
Parallelism
Workload
Speedup
High Performance
Enhancement
Limiting
Coefficient
Experiment

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Park, K., Park, J. S., & Ro, W. W. (2009). Efficient parallelized network coding for P2P file sharing applications. In Advances in Grid and Pervasive Computing - 4th International Conference, GPC 2009, Proceedings (pp. 353-363). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5529). https://doi.org/10.1007/978-3-642-01671-4_32
Park, Karam ; Park, Joon Sang ; Ro, Won Woo. / Efficient parallelized network coding for P2P file sharing applications. Advances in Grid and Pervasive Computing - 4th International Conference, GPC 2009, Proceedings. 2009. pp. 353-363 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Park, K, Park, JS & Ro, WW 2009, Efficient parallelized network coding for P2P file sharing applications. in Advances in Grid and Pervasive Computing - 4th International Conference, GPC 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5529, pp. 353-363, 4th International Conference on Grid and Pervasive Computing, GPC 2009, Geneva, Switzerland, 09/5/4. https://doi.org/10.1007/978-3-642-01671-4_32

Efficient parallelized network coding for P2P file sharing applications. / Park, Karam; Park, Joon Sang; Ro, Won Woo.

Advances in Grid and Pervasive Computing - 4th International Conference, GPC 2009, Proceedings. 2009. p. 353-363 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5529).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - In this paper, we investigate parallel implementation techniques for network coding to enhance the performance of Peer-to-Peer (P2P) file sharing applications. It is known that network coding mitigates peer/piece selection problems in P2P file sharing systems; however, due to the decoding complexity of network coding, there have been concerns about adoption of network coding in P2P file sharing systems and to improve the decoding speed the exploitation of parallelism has been proposed previously. In this paper, we argue that naive parallelization strategies of network coding may result in unbalanced workload distribution and thus limiting performance improvements. We further argue that higher performance enhancement can be achieved through load balancing in parallelized network coding and propose new parallelization techniques for network coding. Our experiments show that, on a quad-core processor system, proposed algorithms exhibit up to 30% of speed-up compared to an existing approach using 1 Mbytes data with 2048×2048 coefficient matrix size.

AB - In this paper, we investigate parallel implementation techniques for network coding to enhance the performance of Peer-to-Peer (P2P) file sharing applications. It is known that network coding mitigates peer/piece selection problems in P2P file sharing systems; however, due to the decoding complexity of network coding, there have been concerns about adoption of network coding in P2P file sharing systems and to improve the decoding speed the exploitation of parallelism has been proposed previously. In this paper, we argue that naive parallelization strategies of network coding may result in unbalanced workload distribution and thus limiting performance improvements. We further argue that higher performance enhancement can be achieved through load balancing in parallelized network coding and propose new parallelization techniques for network coding. Our experiments show that, on a quad-core processor system, proposed algorithms exhibit up to 30% of speed-up compared to an existing approach using 1 Mbytes data with 2048×2048 coefficient matrix size.

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Park K, Park JS, Ro WW. Efficient parallelized network coding for P2P file sharing applications. In Advances in Grid and Pervasive Computing - 4th International Conference, GPC 2009, Proceedings. 2009. p. 353-363. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-01671-4_32