Performance Evaluation of Routing Protocols in DTNs Considering Different Mobility Models

  • Evjola SpahoEmail author
  • Klodian Dhoska
  • Kevin Bylykbashi
  • Leonard Barolli
  • Vladi Kolici
  • Makoto Takizawa
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 927)


In this paper we evaluate the performance of Epidemic, Spray and Wait routing protocols and their versions with congestion control and Epidemic with TCP in Delay Tolerant Networks. For evaluation we used three different mobility models: Random Waypoint (RWP), Steady State Random Waypoint (SSRWP) and a Tirana city map based movement. We used delivery ratio, hop count, average delay and average buffer occupancy metrics to evaluate the network performance. The network performs better for SSRWP compared to RWP and realistic Tirana map-based scenarios. The Epidemic with TCP has a high average delay because of ack packets.


  1. 1.
    Lakkakorpi, J., Ginzboorg, P.: ns-3 module for routing and congestion control studies in mobile opportunistic DTNs. In: Proceedings of Performance Evaluation of Computer and Telecommunication Systems (SPECTS), pp. 1–5 (2013)Google Scholar
  2. 2.
    Lakkakorpi, J., Pitkanen, M., Ott, J.: Using buffer space advertisements to avoid congestion in mobile opportunistic DTNs. In: Proceedings of WWIC, Barcelona, Spain, pp. 1–12, June 2011Google Scholar
  3. 3.
    The ns-3 Network Simulator.
  4. 4.
    Fall, K.: A delay-tolerant network architecture for challenged Internets. In: Proceedings of the International Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, ser. SIGCOMM 2003, pp. 27–34 (2003)Google Scholar
  5. 5.
    Delay- and disruption-tolerant networks (DTNs) tutorial, NASA/JPL’s Interplanetary Internet (IPN) Project (2012).
  6. 6.
    Laoutaris, N., Smaragdakis, G., Rodriguez, P., Sundaram, R.: Delay tolerant bulk data transfers on the Internet. In: Proceedings of the 11th International Joint Conference on Measurement and Modeling of Computer Systems (SIGMETRICS 2009), pp. 229–238 (2009)Google Scholar
  7. 7.
    Cerf, V., Burleigh, S., Hooke, A., Torgerson, L., Durst, R., Scott, K., Fall, K., Weiss, H.: Delay-tolerant networking architecture. IETF RFC 4838 (Informational), April 2007Google Scholar
  8. 8.
    Massri, K., Vernata, A., Vitaletti, A.: Routing protocols for delay tolerant networks: a quantitative evaluation. In: Proceedings of ACM workshop PM2HW2N 2012, pp. 107–114 (2012)Google Scholar
  9. 9.
    Massri, K., Vitaletti, A., Vernata, A., Chatzigiannakis, I.: Routing protocols for delay tolerant networks: a reference architecture and a thorough quantitative evaluation. J. Sens. Actuator Networks, 1–28 (2016).
  10. 10.
    Demmer, M., Fall, K.: DTLSR: delay tolerant routing for developing regions. In: Proceedings of the 2007 ACM Workshop on Networked Systems for Developing Regions, 6 p. (2007)Google Scholar
  11. 11.
    Ilham, A.A., Niswar, M., Agussalim: Evaluated and optimized of routing model on Delay Tolerant Network (DTN) for data transmission to remote area. In: Proceedings of FORTEI, Indonesia University Jakarta, pp. 24–28 (2012)Google Scholar
  12. 12.
    Uchida, N., Ishida, T., Shibata, Y.: Delay tolerant networks-based vehicle-to-vehicle wireless networks for road surveillance systems in local areas. Int. J. Space-Based Situated Comput. 6(1), 12–20 (2016)CrossRefGoogle Scholar
  13. 13.
    Bylykbashi, K., Spaho, E., Barolli, L., Xhafa, F.: Routing in a many-to-one communication scenario in a realistic VDTN. J. High Speed Networks 24(2), 107–118 (2018)CrossRefGoogle Scholar
  14. 14.
    Bylykbashi, K., Spaho, E., Barolli, L., Xhafa, F.: Impact of node density and TTL in vehicular delay tolerant networks: performance comparison of different routing protocols. Int. J. Grid Util. Comput. 7(3), 136–144 (2017)Google Scholar
  15. 15.
    Jain, S., Fall, K., Patra, R.: Routing in a delay tolerant network. In: Proceedings of ACM SIGCOMM 2004 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, Portland, Oregon, USA, 30 August–3 September 2004, pp. 145–158 (2004)Google Scholar
  16. 16.
    Zhang, Z.: Routing in intermittently connected mobile ad hoc networks and delay. IEEE Commun. Surv. Tutorials 8(1), 24–37 (2006)CrossRefGoogle Scholar
  17. 17.
    Soares, V.N.G.J., Rodrigues, J.J.P.C., Farahmand, F.: GeoSpray: a geographic routing protocol for vehicular delay-tolerant networks. Inf. Fusion 15(1), 102–113 (2014)CrossRefGoogle Scholar
  18. 18.
    Burgess, J., Gallagher, B., Jensen, D., Levine, B.N.: Maxprop: routing for vehicle-based disruption-tolerant networks. In: Proceedings of the IEEE Infocom, April 2006Google Scholar
  19. 19.
    Lindgren, A., Doria, A., Davies, E., Grasic, S.: Probabilistic routing protocol for intermittently connected networks. draft-irtf-dtnrg-prophet-09.
  20. 20.
    Vahdat, A., Becker, D.: Epidemic routing for partially connected ad hoc networks. Technical report CS-200006, Duke University, April 2000Google Scholar
  21. 21.
    Spyropoulos, T., Psounis, K., Raghavendra, C.S.: Spray and Wait: an efficient routing scheme for intermittently connected mobile networks. In: Proceedings of ACM SIGCOMM 2005 - Workshop on Delay Tolerant Networking and Related Networks (WDTN-05), Philadelphia, PA, USA, pp. 252–259 (2005)Google Scholar
  22. 22.
    Bylykbashi, K., Spaho, E., Barolli, L., Takizawa, M.: Comparison of spray and wait and epidemic protocols in different DTN scenarios. In: Proceedings of the 12th International Conference on Broad-Band Wireless Computing, Communication and Applications (BWCCA-2017), pp. 218–229 (2017)Google Scholar
  23. 23.
    Spaho, E., Bylykbashi, K., Barolli, L., Takizawa, L.: Routing in a DTN: performance evaluation for random waypoint and steady state random waypoint using NS3 simulator. In: Proceedings of the 12th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC-2017), pp. 133–141 (2017)Google Scholar
  24. 24.
    Navidi, W., Camp, T.: Stationary distributions for the random waypoint mobility model. IEEE Trans. Mob. Comput. 3(1), 99–108 (2004)CrossRefGoogle Scholar
  25. 25.
    Navidi, W., Camp, T., Bauer, N.: Improving the accuracy of random waypoint simulations through steady-state initialization. In: Proceedings of the 15th International Conference on Modeling and Simulation (MS 2004), pp. 319–326, March 2004Google Scholar
  26. 26.
  27. 27.
    Simulation of urban mobility.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Evjola Spaho
    • 1
    Email author
  • Klodian Dhoska
    • 2
  • Kevin Bylykbashi
    • 3
  • Leonard Barolli
    • 4
  • Vladi Kolici
    • 1
  • Makoto Takizawa
    • 5
  1. 1.Department of Electronics and Telecommunication, Faculty of Information TechnologyPolytechnic University of TiranaTiranaAlbania
  2. 2.Department of Production-Management, Faculty of Mechanical EngineeringPolytechnic University of TiranaTiranaAlbania
  3. 3.Graduate School of EngineeringFukuoka Institute of Technology (FIT)Higashi-KuJapan
  4. 4.Department of Information and Communication EngineeringFukuoka Institute of Technology (FIT)Higashi-KuJapan
  5. 5.Department of Advanced SciencesHosei UniversityKoganei-shiJapan

Personalised recommendations