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Anycast in Delay Tolerant Networks

This paper presents a novel routing metric called Expected Multi-Destination Delay for Anycast (EMDDA) to improve performance in Delay Tolerant Networks (DTNs), where direct end-to-end paths are unreliable. We explore the challenges of unpredictable connectivity and storage limitations through a practical scenario, like sharing files at a music festival. Our simulation results indicate that employing EMDDA can reduce average delivery delays by 11.3% and storage requirements by 19.2% compared to traditional methods. Future research will focus on optimizing trade-offs between delivery time and storage constraints.

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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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