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Practical routing in delay-tolerant networks
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Source Applications, Technologies, Architectures, and Protocols for Computer Communication archive
Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking table of contents
Philadelphia, Pennsylvania, USA
Pages: 237 - 243  
Year of Publication: 2005
ISBN:1-59593-026-4
Authors
Evan P. C. Jones  University of Waterloo, Waterloo, ON, Canada
Lily Li  University of Waterloo, Waterloo, ON, Canada
Paul A. S. Ward  University of Waterloo, Waterloo, ON, Canada
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Delay-tolerant networks (DTNs) have the potential to connect devices and areas of the world that are under-served by current networks. A critical challenge for DTNs is determining routes through the network without ever having an end-to-end connection, or even knowing which "routers" will be connected at any given time. Prior approaches have focused either on epidemic message replication or on knowledge of the connectivity schedule. The epidemic approach of replicating messages to all nodes is expensive and does not appear to scale well with increasing load. It can, however, operate without any prior network configuration. The alternatives, by requiring a priori connectivity knowledge, appear infeasible for a self-configuring network.In this paper we present a practical routing protocol that only uses observed information about the network. We designed a metric that estimates how long a message will have to wait before it can be transferred to the next hop. The topology is distributed using a link-state routing protocol, where the link-state packets are "flooded" using epidemic routing. The routing is recomputed when connections are established. Messages are exchanged if the topology suggests that a connected node is "closer" than the current node.We demonstrate through simulation that our protocol provides performance similar to that of schemes that have global knowledge of the network topology, yet without requiring that knowledge. Further, it requires a significantly smaller quantity of buffer, suggesting that our approach will scale with the number of messages in the network, where replication approaches may not.


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  21

Collaborative Colleagues:
Evan P. C. Jones: colleagues
Lily Li: colleagues
Paul A. S. Ward: colleagues