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Anycast in Delay Tolerant Networks

Anycast in Delay Tolerant Networks. Yili Gong, Yongqiang Xiong, Qian Zhang, Zhensheng Zhang, Wenjie Wang and Zhiwei Xu Yili Gong Indiana University Globecom, Nov. 29, 2006. Outline. Introduction Anycast Routing Metric – EMDDA Anycast Routing Algorithm Performance Evaluation

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Anycast in Delay Tolerant Networks

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  1. Anycast in Delay Tolerant Networks Yili Gong, Yongqiang Xiong, Qian Zhang, Zhensheng Zhang, Wenjie Wang and Zhiwei Xu Yili Gong Indiana University Globecom, Nov. 29, 2006

  2. Outline • Introduction • Anycast Routing Metric – EMDDA • Anycast Routing Algorithm • Performance Evaluation • Conclusions & Future Work

  3. Introduction • Anycast • A service that allows a node to send a message to at least one, and preferably only one, of the members in a group. • Delay Tolerant Network (DTN) • No end-to-end contemporaneous path is guaranteed between any two nodes.

  4. Challenges • Uncontrollable movement • The unpredictability of network connectivity and delay • Limited storage capacity

  5. Scenario • Music festival • People cluster to watch performances • Cars, shuttle buses or people move between clusters • To share music files

  6. Related Work • Anycast routing in the Internet and mobile ad hoc networks • Unicast routing in DTN • Vahdat and Becker [TR’00]: flooding • Tan [GLOBECOM'03]: SEPR • Zhao [ICC’05]: exploiting non-randomness movement • Jain [WDTN'05] & Jones [WDTN'05]: MED (Minimum Expected Delay ) • Multicast routing in DTN • Zhao [WDTN'05]: semantics models

  7. Network Model • G = (V, E) • An edge e is characterized by • Source u and destination v • w(u, v): PDF of the departure time of mobile devices leaving from u to v • d(u, v): Moving delay • c(u, v): Storage capacity of a mobile device

  8. Assumptions • Nodes in the network are stationary and generate messages, while mobile devices do not generate messages themselves. • On each edge, the mobile devices have the same storage capacity and moving speed. • On each edge, the departure time of mobile devices follows Poisson distributions.

  9. Unicast Routing Metric • MED (Minimum Expected Delay) • Average waiting time as the weight of an edge. • PED (Practical Expected Delay) • Expectation of different paths as the weight. x E(w(x, d))=100 E(w(s, x))=100 d s y E(w(y, d))=20 E(w(s, y))=1000

  10. Anycast Routing Metric • EMDDA (Expected Multi-Destination Delay for Anycast ) • Expectation of different paths to different destinations as the weight. E(w(x, d1))=100 d1 x E(w(s, x))=100 s d2 y E(w(s, y))=1000 E(w(y, d2))=20

  11. Anycast Routing Algorithm Based on EMDDA • On node u, a message, heading for anycast group D, is waiting. • When a mobile device is about to leave for node v, • If d(u,v)+EMDDA(v,D) < EMDDA(u,D), then upload the message onto the mobile device. • Or, do nothing.

  12. Experiment Setup • A random graph of 100 nodes • Generated by Waxman Network Topology Generator • The mean interval time of mobile device leaving on each edge is selected randomly from 600 to 6,000 seconds. • The moving delay, or single-hop delay, on each edge is a number between 60 and 600 seconds, which is in proportion to the distance between the nodes. • Assume that the storage capacities of mobile devices are the same and they vary from 300 to 800 messages.

  13. Performance Metrics • Anycast Delivery Delay (ADD) • The time it takes to route this message from its sender to any node in its anycast destination group. • Average Anycast Delivering Delay (AADD) • The average ADD of all anycast sessions in the network. • Average Max Queue Length • The average of the max queue lengths on all the nodes.

  14. CDF of Anycast Delivery Delay (ADD) Here the mean message inter-arrival time is 100 seconds and the mobile device storage capacity is 300 messages.

  15. AADD with Hop Number Here, the mean message inter-arrival time is 100 seconds and the mobile device storage capacity is 300 messages.

  16. Average Max Queue Lengthwith Mean Message Inter-Arrival Time Here the mobile device storage capacity is 300 messages.

  17. Conclusion & Future Work • Conclusions • The proposed novel routing metric, EMDDA, depicts the practical delay for anycast more accurately. • The simulation results show that the routing algorithm based on EMDDA can reduce the average delay by 11.3% on average compared to MED and reduce the required storage by 19.2% on average. • Future Work • To find the tradeoff between the delivery time and the storage by adjusting the number of message copies. • To extend the anycast routing algorithm to incorporate both node storage constraint and network traffic dynamics.

  18. Any Questions?

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