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Assessment Model for Opportunistic Routing

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Due to the increased capabilities of mobile devices and through wireless opportunistic contacts, users can experience new ways to share and retrieve content anywhere and anytime, even in the presence …

Due to the increased capabilities of mobile devices and through wireless opportunistic contacts, users can experience new ways to share and retrieve content anywhere and anytime, even in the presence of link intermittency. Due to the significant number of available routing solutions, it is difficult to understand which one has the best performance, since all of them follow a different evaluation method. This paper proposes an assessment model, based on a new taxonomy, which comprises an evaluation guideline with performance metrics and experimental setup to aid designers in evaluating solutions through fair comparisons. Simulation results based on the proposed model revisit the performance results published by Epidemic, PROPHET, and BubbleRap, showing how they perform under the same set of metrics and scenario.

This presentation was given in the IEEE 3rd Latin-American Conference on Communications (LATINCOM), on Oct 24th, 2011, in Belém/PA, Brazil.
http://www.ieee-latincom.ufpa.br/

Published in: Technology, Health & Medicine
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  • 1. Assessment Model for Opportunistic Routing Waldir Moreira, Paulo Mendes, and Susana Sargento waldir.junior@ulusofona.pt Oct 24th, 2011 IEEE Latincom 2011, Belém-PA/Brasil
  • 2. Agenda• Introduction• Carried Analysis• Our Work• Evaluation and Results• Conclusions and Future Work 2
  • 3. Introduction• Powerful devices• Spontaneous networks• Opportunistic contacts - Intermittent connectivity 3
  • 4. Motivation• Many routing solutions - Epidemic, encounter history, social aspects ...• Different classifications - Identify different families - Application requirements to algorithm mapping• Different performance metrics and experimental setups 4
  • 5. Goal• Clear classification of solutions• Fair way to assess routing performance - Importance of a homogeneous evaluation - Parameter setups and performance metrics can favour some proposals 5
  • 6. Close Look atDifferent Proposals 6
  • 7. Performance MetricIdentification 7
  • 8. Existing Classifications 8
  • 9. Proposed Taxonomy• Identify common aspects of solutions - Routing strategy and metrics 9
  • 10. Universal EvaluationFramework• Performance metrics - Delivery probability, cost, and delay• Experimental setup - Network density (area, # of nodes, ...) - Traffic (sources/destinations, load, ...) 10
  • 11. Scenario• Heterogenous mobility - Human (Working Day Movement) - Veicular (Bus Movement) - Random (Shortest Path Map-Based Mov.)• Nodes belonging to different home/office/entertainment location• Epidemic, PROPHET, and BubbleRap 11
  • 12. Results• Epidemic vs. PROPHET - Better performance - ~2.1x for Epidemic - ~2.6x for PROPHET - From 22% to ~46% 12
  • 13. Results• Epidemic vs. PROPHET - More forwardings - Over 44x for Epidemic - Over 34x for PROPHET - From 12% to 47% 13
  • 14. Results• Epidemic vs. PROPHET - Greater delay - ~5.5x for Epidemic - ~9.5x for PROPHET - From ~27% to ~37% 14
  • 15. Results• PROPHET vs. BubbleRap - Better performance - 55% for PROPHET - 33% for BubbleRap - Over 17 perc. points 15
  • 16. Results• PROPHET vs. BubbleRap - Cost from ~40% to ~70% 16
  • 17. Conclusions andFuture Work• For fair assessment - Imperative to consider similar conditions - Same performance metrics• Both taxonomy and UEF should be updated to comply with future new trends 17
  • 18. Acknowledgements• To FCT for financial support via PhD grant (SFRH/BD/62761/2009) and UCR project (PTDC/EEA-TEL/103637/2008) 18
  • 19. Assessment Model for Opportunistic Routing Waldir Moreira, Paulo Mendes, and Susana Sargento waldir.junior@ulusofona.pt Oct 24th, 2011 IEEE Latincom 2011, Belém-PA/Brasil

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