Supernode routing: a grid-based message passing scheme for sparse opportunistic networks

  • Deepak Kumar Sharma
  • Deepika KukrejaEmail author
  • Samarth Chugh
  • Shubham Kumaram
Original Research


In opportunistic networks (Oppnets), messages are transferred from one node to another when the opportunity arrives and until then, these messages are stored in their buffers. Challenges in such scenarios can arise due to multiple reasons such as buffer space, energy limitations, density of nodes and sparse networks. This paper takes into consideration these factors and proposes a novel routing protocol. Supernode routing is proposed for networks in which nodes are organised in clusters, also known as cells, and takes advantage of this property to limit flooding. Special nodes called supernodes are utilised to transmit a message from one cell to another. Nodes within cells forward their messages to the optimal supernodes based on the direction of the destination cell. The messages are propagated by flooding in intermediate cells until the message is passed over to the next cell in the path using supernodes. When the message is transferred to another cell, it is dropped from all nodes in the current cell. In this manner, messages are streamlined to an expected path to an extent, based on the sender and receiver. This is in contrast to random paths of messages found in most other protocols. The proposed model has been simulated in spatially separated scenarios using ONE simulator. It has high delivery probabilities with drastically low overhead ratios in comparison to the other existing routing protocols.


Opportunistic network ONE simulator Store-carry-forward mechanism Delay tolerant networks Wireless networks Routing protocol Energy-aware Sparse networks Sensor network Controlled flooding 



  1. Boldrini C, Conti M, Jacopini J, Passarella A (2007) Hibop: a history based routing protocol for opportunistic networks. In: World of wireless, mobile and multimedia networks, 2007. WoWMoM 2007. IEEE international symposium. IEEE, pp 1–12Google Scholar
  2. Borah SJ, Dhurandher SK, Woungang I et al (2017) A multi-objectives based technique for optimized routing in opportunistic networks. J Ambient Intell Humaniz Comput. Google Scholar
  3. Burgess J, Gallagher B, Jensen D, Levine BN (2006) Maxprop: routing for vehicle-based disruption-tolerant networks. In: INFOCOM 2006. 25th IEEE international conference on computer communications. Proceedings, IEEE, pp 1–11Google Scholar
  4. Dhurandher SK, Sharma DK, Woungang I, Chao H (2011) Performance evaluation of various routing protocols in opportunistic networks. In: 2011 IEEE GLOBECOM workshops (GC Wkshps), pp 1067–1071.
  5. Dhurandher SK, Sharma DK, Woungang I, Gupta R, Garg S (2014) Gaer: genetic algorithm-based energy-efficient routing protocol for infrastructure-less opportunistic networks. J Supercomput 69(3):1183–1214CrossRefGoogle Scholar
  6. Dhurandher SK, Borah SJ, Obaidat MS, Sharma DK, Gupta S, Baruah B (2015) Probability-based controlled flooding in opportunistic networks. In: e-business and telecommunications (ICETE), 2015 12th international joint conference, vol 6. IEEE, pp 3–8Google Scholar
  7. Dhurandher SK, Borah S, Woungang I, Sharma DK, Arora K, Agarwal D (2016a) Edr: an encounter and distance based routing protocol for opportunistic networks. In: Advanced information networking and applications (AINA), 2016 IEEE 30th international conference. IEEE, pp 297–302Google Scholar
  8. Dhurandher SK, Woungang I, Arora J, Gupta H (2016b) History-based secure routing protocol to detect blackhole and greyhole attacks in opportunistic networks. Recent Adv Commun Netw Technol (Formerly Recent Patents on Telecommunication) 5(2):73–89Google Scholar
  9. Dhurandher SK, Sharma DK, Woungang I, Saini A (2017) An energy-efficient history-based routing scheme for opportunistic networks. Int J Commun Syst 30(7):e2989. CrossRefGoogle Scholar
  10. Fall K (2003) A delay-tolerant network architecture for challenged internets. In: Proceedings of the 2003 conference on applications, technologies, architectures, and protocols for computer communications, SIGCOMM ’03. ACM, New York, pp 27–34.
  11. Jain S, Fall K, Patra R (2004) Routing in a delay tolerant network. SIGCOMM Comput Commun Rev 34(4):145–158. CrossRefGoogle Scholar
  12. Keränen A, Ott J, Kärkkäinen T (2009) The one simulator for dtn protocol evaluation. In: Proceedings of the 2nd international conference on simulation tools and techniques, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), Simutools ’09. ICST, Brussels, pp 55:1–55:10.
  13. Lilien L, Kamal ZH, Bhuse V, Gupta a (2006) Opportunistic networks: the concept and research challenges. In: Int workshop on research challenges in security and privacy for mobile and wireless networks, pp 1–36Google Scholar
  14. Lin CY, Chung JY, Li CT, Hu CL, Lien YN (2017) Geo-routing with angle-based decision in delay-tolerant networks. In: Ubi-media computing and workshops (Ubi-Media), 2017 10th international conference. IEEE, pp 1–5Google Scholar
  15. Lindgren A, Doria A, Schelen O (2003) Probabilistic routing in intermittently connected networks. ACM SIGMOBILE Mob Comput Commun Rev 7(3):19–20. CrossRefGoogle Scholar
  16. Musolesi M, Hailes S, Mascolo C (2005) Adaptive routing for intermittently connected mobile ad hoc networks. In: World of wireless mobile and multimedia networks, 2005. WoWMoM 2005. 6th IEEE international symposium. IEEE, pp 183–189Google Scholar
  17. Sharma DK, Dhurandher SK, Woungang I, Bansal A, Gupta A (2017) GD-CAR: a genetic algorithm based dynamic context aware routing protocol for opportunistic networks. In: International conference on network-based information systems. Springer, Toronto, pp 611–622Google Scholar
  18. Sharma DK, Dhurandher SK, Agarwal D, Arora K (2018a) krop: k-means clustering based routing protocol for opportunistic networks. J Ambient Intell Humaniz Comput. Google Scholar
  19. Sharma DK, Dhurandher SK, Woungang I, Srivastava RK, Mohananey A, Rodrigues JJPC (2018b) A machine learning-based protocol for efficient routing in opportunistic networks. IEEE Syst J.
  20. Spyropoulos T, Psounis K, Raghavendra CS (2005) Spray and wait: an efficient routing scheme for intermittently connected mobile networks. In: Proceedings of the 2005 ACM SIGCOMM workshop on delay-tolerant networking (WDTN ’05), Philadelphia, PA, USA, 22–26 August 2005, pp 252–259Google Scholar
  21. Vahdat A, Becker D et al (2000) Epidemic routing for partially connected ad hoc networks. Technical report number CS-200006, Duke University, pp 1–14Google Scholar
  22. Zhao R, Wang X, Zhang L, Lin Y (2017) A social-aware probabilistic routing approach for mobile opportunistic social networks. Trans Emerg Telecommun Technol 28(12):e3230. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Deepak Kumar Sharma
    • 1
  • Deepika Kukreja
    • 1
    Email author
  • Samarth Chugh
    • 1
  • Shubham Kumaram
    • 1
  1. 1.Department of Information TechnologyNSIT, University of DelhiNew DelhiIndia

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