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Study of a bus-based disruption-tolerant network: mobility modeling and impact on routing
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International Conference on Mobile Computing and Networking archive
Proceedings of the 13th annual ACM international conference on Mobile computing and networking table of contents
Montréal, Québec, Canada
SESSION: Mobility/interference models table of contents
Pages: 195 - 206  
Year of Publication: 2007
ISBN:978-1-59593-681-3
Authors
Xiaolan Zhang  University of Massachusetts
Jim Kurose  University of Massachusetts
Brian Neil Levine  University of Massachusetts
Don Towsley  University of Massachusetts
Honggang Zhang  Suffolk University
Sponsors
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

We study traces taken from UMass DieselNet, a Disruption-Tolerant Network consisting of WiFi nodes attached to buses. As buses travel their routes, they encounter other buses and in some cases are able to establish pair-wise connections and transfer data between them. We analyze the bus-to-bus contact traces to characterize the contact process between buses and its impact on DTN routing performance. We find that the all-bus-pairs aggregated inter-contact times show no discernible pattern. However, the inter-contact times aggregated at a route level exhibit periodic behavior.Based on analysis of the deterministic inter-meeting times for bus pairs running on route pairs, and consideration of the variability in bus movement and the random failures to establish connections, we construct generative route-level models that capture the above behavior. Through trace-driven simulations of epidemic routing, we find that the epidemic performance predicted by traces generated with this finer-grained route-level model is much closer to the actual performance that would be realized in the operational system than traces generated using the coarse-grained all-bus-pairs aggregated model. This suggests the importance in choosing the rightlevel of model granularity when modelingmobility-related measures such as inter-contact times in DTNs.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  23

Collaborative Colleagues:
Xiaolan Zhang: colleagues
Jim Kurose: colleagues
Brian Neil Levine: colleagues
Don Towsley: colleagues
Honggang Zhang: colleagues