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Abstract

This paper tries to address the challenge of detecting and managing overlay topologies in opportunistic networks. As a first contribution, it introduces the concept of "link" in opportunistic networks, which is different from the traditional perspective in classic MANETs: instead of an instantaneous communication relation between two nodes, links are defined here as the cumulative contacts of nodes over a time interval. This redefinition lets opportunistic networks be modeled as graphs that evolve. A key insight is that this approach enables the regulation of how nodes handle contacts to construct overlays according to a desired topology. That is important because the statistical properties of the overlay topology can form a basis for assessing a network's capacity to disseminate content. The feasibility of the proposed method is shown by a trace-driven simulation using various datasets, which range from dense urban networks to highly sparse environments. These experiments confirm that the approach effectively manages overlay topologies in opportunistic networks.

Keywords

MANET DTN QoS OMN

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How to Cite
Jolimbetova Elyanora. (2024). Designing And Optimizing Opportunistic Communication Networks. Texas Journal of Engineering and Technology, 39, 17–21. https://doi.org/10.62480/tjet.2024.vol39.pp17-21

References

  1. Fall, K. (2003). A Delay-Tolerant Network Architecture for Challenged Internets. SIGCOMM '03:
  2. Proceedings of the 2003 Conference on Applications, Technologies, Architectures, and Protocols for
  3. Computer Communications, 27–34. [DOI: 10.1145/863955.863960]
  4. Kempe, D., Kleinberg, J., & Kumar, A. (2000). Connectivity and Inference Problems for Temporal
  5. Networks. STOC '00: Proceedings of the 32nd ACM Symposium on Theory of Computing, 513–522. [DOI:
  6. 1145/335305.335347]
  7. Burgess, J., Gallagher, B., Jensen, D., & Levine, B. N. (2006). MaxProp: Routing for Vehicle-Based
  8. Disruption-Tolerant Networks. Proceedings of IEEE INFOCOM, 11(4), 1–11. [DOI:
  9. 1109/INFOCOM.2006.228]
  10. Perkins, C. E., Royer, E. M., & Das, S. R. (2003). Ad Hoc On-Demand Distance Vector (AODV)
  11. Routing. RFC Editor. [https://doi.org/10.17487/rfc3561]
  12. Bluetooth SIG. (2009). Bluetooth Core Specification Version 4.0.
  13. [https://www.bluetooth.com/specifications/specs/core-specification/]
  14. Hossmann, T., Spyropoulos, T., & Legendre, F. (2011). From Contacts to Graphs: Pitfalls in Using
  15. Complex Network Analysis for DTN Routing. IEEE INFOCOM, 858–866. [DOI:
  16. 1109/INFCOM.2011.5934898]
  17. Vahdat, A., & Becker, D. (2000). Epidemic Routing for Partially-Connected Ad Hoc Networks.
  18. Technical Report CS-2000-06, Duke University.
  19. [https://www.cs.duke.edu/ari/courses/fall06/cps296.3/papers/2000-vahdat-epidemic-routing.pdf]
  20. Scellato, S., Mascolo, C., Musolesi, M., & Latora, V. (2011). Distance Matters: Geo-social Metrics
  21. for Online Social Networks. Proceedings of the 3rd Conference on Online Social Networks (WOSN), 8–14.
  22. [DOI: 10.1145/1991023.1991027]
  23. Liang, Y., & Lee, J. (2006). Spatiotemporal Dataset Analysis for Wireless Mobile Networks.
  24. National University of Singapore. [https://nuswirelessmobilitydatasets.com]
  25. Newman, M. E. J. (2003). The Structure and Function of Complex Networks. SIAM Review, 45(2),
  26. –256. [DOI: 10.1137/S003614450342480]