Advertisement

An analytical study of the main characteristics of Cluster-based Energy-aware Virtual Ring Routing (CLEVER): Number of clusters, number of hops and cluster diameter

  • Ghofrane FersiEmail author
  • Maher Ben Jemaa
Article
  • 36 Downloads

Abstract

Cluster-based Energy aware Virtual Ring Routing (CLEVER) is an energy-aware routing protocol for randomly deployed heterogeneous Wireless Sensor Networks (WSN). It proposes a novel clustering scheme where each cluster is made up of energy-powerful nodes at the range of each others. This strategy restraints the use of energy-constrained nodes to the areas that are uncovered by clusters in order to extend their lifetime. In our previous work we have evaluated CLEVER over a small network and with medium scale simulations that have shown the drastic improvement of the network performance. In this paper, we propose an analytical study of CLEVER that estimates the number, the size of formed clusters as well as areas that are only covered by weak nodes. This provides an accurate study of the protocol performance when the number of nodes increases significantly and also when the surface area of our network becomes extremely large. Our proposed study have proved that CLEVER exhibits significantly good performance.

Keywords

Analytical study CLEVER Randomly deployed Wireless Sensor Networks Number and size of covered areas 

Notes

Acknowledgments

We thank Dr. Wassef LOUATI for assistance in our proposed protocol CLEVER: Cluster-based Energy-aware Virtual Ring Routing.

References

  1. 1.
    Arioua M, el Assari Y, Ez-zazi I, el Oualkadi A (2016) Multi-hop Cluster Based Routing Approach for Wireless Sensor Networks. Proced Comput Sci 83:584–591CrossRefGoogle Scholar
  2. 2.
    Sarika Y, Rama SY (2016) A review on energy efficient protocols in wireless sensor networks. J Wirel Netw 22:335–350CrossRefGoogle Scholar
  3. 3.
    Akyildiz IF, Su W, Sankarasubramaniam Y, cayirci E (2008) Wireless sensor networks: a survey. Comput Netw 38:393–422CrossRefGoogle Scholar
  4. 4.
    Ruiz M, Alvarez E, Serrano A, Garcia E (2016) The convergence between wireless sensor networks and the internet of things; challenges and perspectives: a survey. IEEE Latin Amer Trans 14(10):4249–4254CrossRefGoogle Scholar
  5. 5.
    Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52:2292–2330CrossRefGoogle Scholar
  6. 6.
    Isabel D, Falko D (2009) On the lifetime of wireless sensor networks. ACM Trans Sensor Netw 5:1–39Google Scholar
  7. 7.
    Fersi G, Louati W, Ben Jemaa M (2016) CLEVER: Cluster-based Energy-aware Virtual Ring Routing in randomly deployed wireless sensor networks. Peer-to-Peer Netw Appl 9(4):640–655. SpringerCrossRefGoogle Scholar
  8. 8.
    Fan X, Song Y (2007) Improvement on LEACH Protocol of Wireless Sensor Network. Proceedings of the International Conference on Sensor Technologies and Applications, Valencia. IEEE, USA, pp 260–264Google Scholar
  9. 9.
    Fersi G, Louati W, Ben Jemaa M (2013) Distributed Hash table-based routing and data management in wireless sensor networks: a survey. Wirel Netw 19(2):219–236. ACM/SpringerCrossRefGoogle Scholar
  10. 10.
    Muneeb A, Koen L (2007) A Case for Peer-to-Peer Network Overlays in Sensor Networks. In: Proceedings of the International Workshop on Wireless Sensor Network Architecture (WWSNA) with 6th IPSN, Cambridge, pp 56–61Google Scholar
  11. 11.
    Sioutas S, Oikonomou K, Papaloukopoulos G (2009) Building an Efficient P2P Overlay for Energy-Level Queries in Sensor Networks. In: Proceedings of the International Conference on Management of Emergent Digital EcoSystems (MEDES’09), Lyon, France. ACM, New YorkCrossRefGoogle Scholar
  12. 12.
    Wang Y, Wang X, Agrawal DP, Minai AA Impact of Heterogeneity on Coverage and Broadcast Reachability in Wireless Sensor Networks. In: Proceedings of the International Conference on Computer Communications and Networks (ICCCN06), Arlington, pp 63–67Google Scholar
  13. 13.
    Matthew C, Miguel C, Edmund BN, Greg O, Antony R (2006) Virtual Ring Routing: Network Routing Inspired by DHTs. In: Proceedings of the SIGCOMM. ACM, Pisa, pp 351–362,Google Scholar
  14. 14.
    Fersi G, Louati W, Ben Jemaa M (2013) The optimal transmitting power in randomly deployed heterogeneous Wireless Sensor Networks for predetermined average node degree. In: Proceedings of the 9th International Wireless Communications & Mobile Computing Conference (IWCMC 2013), CagliariGoogle Scholar
  15. 15.
    Xing G, Lu C, Zhang Y, Huang Q, Pless R (2007) Minimum power configuration for wireless communication in sensor networks. ACM Transactions on Sensor Networks:3Google Scholar
  16. 16.
    Mack C (1954) The expected number of clumps when convex laminae are placed at random and with random orientation on a plane area. Proc Camb Phil Soc 50:581–585MathSciNetCrossRefGoogle Scholar
  17. 17.
    Kellerer AM (1983) On the number of clumps resulting from the overlap of randomly placed figures in a plane. J Appl Probab 20:126–135MathSciNetCrossRefGoogle Scholar
  18. 18.
    NS2 website Available at http://www.isi.edu/nsnam/ns/
  19. 19.
    Malkhi D, Sen S, Talwar K, Werneck R, Wieder U (2009) Virtual ring routing trends. In: Proceedings of the 23rd international conference on distributed computing, Berlin HeidelbergGoogle Scholar
  20. 20.
    Fersi G, Louati W, Ben Jemaa M (2013) Energy-Aware Distributed Hash Table based Bootstrapping Protocol for Randomly Deployed Heterogeneous Wireless Sensor Networks. In: 28th International Symposium on Computer and Information Sciences (Iscis 2013). Springer, ParisCrossRefGoogle Scholar
  21. 21.
    Fersi G, Louati W, Ben Jemaa M (2013) Consistent and Efficient Bootstrapping Ring-Based Protocol in Randomly Deployed Wireless Sensor Networks. In: IEEE 20th International conference on Telecommunications (ICT 2013). IEEE Communications Society, MarocGoogle Scholar
  22. 22.
    Fersi G, Louati W, Ben Jemaa M (2013) Time Estimation of a Ring-based Bootstrapping Protocol in Wireless Sensor Networks. In: IEEE LiveCity Workshop on Smart and Pervasive Communications for Enhanced Communities (LiveCity 2013). IEEE Communication Society, ParisGoogle Scholar
  23. 23.
    Ammari MH (2009) Challenges and Opportunities of Connected k-Covered Wireless Sensor Networks. Studies in Computational Intelligence. Springer, BerlinCrossRefGoogle Scholar
  24. 24.
    Pallavi S, Smruti RS (2017) Internet of things: architectures, Protocols, and Applications. Journal of Electrical and Computer Engineering 2017Google Scholar
  25. 25.
    Evans D (2011) The internet of things how the next evolution of the internet is changing everything cisco internet business solutions group (IBSG), White paperGoogle Scholar
  26. 26.
    Friis HT (1946) A Note on a Simple Transmission Formula, In: Proceedings of the I.R.E. and Waves and Electrons, pp 254256CrossRefGoogle Scholar
  27. 27.
    Miorandi D, Altman E, Alfano G (2008) The impact of channel randomness on coverage and connectivity of ad hoc and sensor networks. IEEE Trans Wirel Commun 7(3):1062–1072CrossRefGoogle Scholar
  28. 28.
    Liu B, Otis B, Challa S, Axon P, Chou CT, Jha S (2006) On the Fading and Shadowing Effects for Wireless Sensor Networks, IEEE International Conference on Mobile Adhoc and Sensor Systems (MASS)Google Scholar
  29. 29.
    Gopakumar A, Jacob L (2011) Power-aware range-free wireless sensor network localization using neighbor distance distribution. International Journal of Wireless Communications and Mobile Computing, Wiley, New YorkGoogle Scholar
  30. 30.
    Wan P-J, Yi C-W Coverage by Randomly Deployed Wireless Sensor Networks, Proceedings of the 2005 Fourth IEEE International Symposium on Network Computing and Applications (NCA05)Google Scholar
  31. 31.
    Senouci MR, Mellouk A, Aissani A (2014) Random deployment of wireless sensor networks: a survey and approach. Int J Ad Hoc Ubiquit Comput 15(1/2/3):133146CrossRefGoogle Scholar
  32. 32.
    Zhang H, Hou J (2004) On deriving the upper bound of α-lifetime for large sensor networks, In: Proceedings of the 5th ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 04, New York, pp 121132Google Scholar
  33. 33.
    Fersi G (2015) A distributed and flexible architecture for Internet of Things. Procedia Comput Sci 73:130–137CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science and Applied Mathematics, National School of Engineers of Sfax, Research Laboratory of Development and Control of Distributed Applications (ReDCAD)University of SfaxBPTunisia
  2. 2.Higher Institute of Applied Sciences and Technology of Sousse (ISSAT Sousse)University of SousseSousseTunisia

Personalised recommendations