Assessment Model for Opportunistic Routing
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The authors propose a taxonomy and universal evaluation framework to assess opportunistic routing algorithms. They classify existing routing solutions and identify common performance metrics like delivery probability, cost, and delay. An evaluation of Epidemic, PROPHET, and BubbleRap routing under different mobility models shows that Epidemic and PROPHET have higher delivery rates but also greater costs and delays than BubbleRap. The proposed taxonomy and evaluation framework aim to provide a fair and standardized way to compare opportunistic routing algorithms.
Assessment Model for Opportunistic Routing
- 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 at Different Proposals 6
- 9. Proposed Taxonomy • Identify common aspects of solutions - Routing strategy and metrics 9
- 10. Universal Evaluation Framework • 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 and Future 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