Skip to main content

Advertisement

SpringerLink
Log in

An ant-swarm inspired dynamic multiresolution data dissemination protocol for wireless sensor networks

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

One of the main concerns of wireless sensor networks (WSNs) is to deliver useful information from data sources to users at a minimum power consumption due to constraints that sensor nodes must operate on limited power sources for extended time. In particular, achieving power-efficiency and multihop communication in WSN applications is a major issue. This paper continues on the investigation of a recently proposed Minimum-power Multiresolution Data Dissemination (MMDD) problem for WSNs (whose solution is considered here as a benchmark). We propose an ant-inspired solution to this problem. To the best of our knowledge, no attempts have been made so far in this direction. We have evaluated the performance of our proposed solution by conducting a variety of experiments and have found our solution to be promising in terms of total energy consumption in data dissemination.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Xing G, Li M, Luo H, Jia X (2009) Dynamic multiresolution data dissemination in wireless sensor networks. IEEE Trans Mob Comput 8(9):1205–1220

    Article  Google Scholar 

  2. Dorigo M, Birattari M, Stützle T (2006) Ant colony optimization—artificial ants as a computational intelligence technique. IEEE Comput Intell Mag 1:28–39

    Google Scholar 

  3. Al-Karaki JN, Kamal AE (2004) Routing techniques in wireless sensor networks: a survey. IEEE Wirel Commun 11:6–28

    Article  Google Scholar 

  4. Zabin F, Misra S, Woungang I, Rashvand HF, Ma N-W, Ahsan Ali M (2008) REEP: data-centric, energy-efficient and reliable routing protocol for wireless sensor networks. IET Commun 2(8):995–1008

    Article  Google Scholar 

  5. Ben Hamida E, Chelius G (2008) Strategies for data dissemination to mobile sinks in wireless sensor networks. IEEE Wirel Commun 15(6):31–37

    Article  Google Scholar 

  6. Wu X, Che G (2007) Dual-sink: using mobile and static sinks for lifetime improvement in wireless sensor networks. In: Proceedings of 16th international conference on computer communications and networks (ICCCN’07), Honolulu, HI, USA, 13–16 August 2007, pp 1297–1302

    Chapter  Google Scholar 

  7. Wang Y-H, Huang K-F, Huang Y-M, Tsao S-W (2011) An instantaneous data dissemination mechanism with mobile sinks in wireless sensor network. In: Proceedings of IEEE international conference on advanced information networking and applications (AINA’11), Biopolis, Singapore, 22–25 March 2011, pp 22–25. pp 385–390

    Google Scholar 

  8. Faheem Y, Boudjit S, Chen K (2009) Data dissemination strategies in mobile sink wireless sensor networks: a survey. In: Proceedings of 2nd IFIP wireless days (WD), Paris, 15–17 December 2009, pp 1–6

    Google Scholar 

  9. Intanagonwiwat C, Govindan R, Estrin D (2000) Directed diffusion: a scalable and robust communication paradigm for sensor networks. In: Proceedings of the sixth annual ACM/IEEE international conference on mobile computing and networking (MobiCom 2000), Boston, MA, USA, August 2000, ACM, New York, pp 56–67

    Chapter  Google Scholar 

  10. Heinzelman WR, Kulik J, Balakrishnan H (1999) Adaptive protocols for information dissemination in wireless sensor networks. In: Proceedings Mobicom ‘99, Seattle, USA, 15–20 August 1999 pp 174–185

    Chapter  Google Scholar 

  11. Yadav RK, Gupta K, Yadav AS (2011) Comparison of data dissemination protocols for wireless sensor networks. Int J Sci Eng Res 2(7):37–49

    Google Scholar 

  12. Ye F, Luo H, Cheng J, Lu S, Zhang L (2002) A two-tier data dissemination model for large-scale wireless sensor networks. In: Proceedings ACM MobiCom, pp 148–159

    Google Scholar 

  13. Zhou Z, Xiang X, Wang X (2006) An energy efficient data dissemination protocol in wireless sensor networks. In: Proceedings of the international symposium on a world of wireless, mobile and multimedia networks, June 2006

    Google Scholar 

  14. Machado M, Goussevskaia O, Mini R, Rezende C, Loureiro A, Mateus G, Nogueira J (2005) Data dissemination in autonomic wireless sensor networks. IEEE J Sel Areas Commun 23(12):2305–2319

    Article  Google Scholar 

  15. Lu S, Ye F, Zhong G, Zhang L (2003) Gradient broadcast: a robust data delivery protocol for large scale sensor networks. In: IPSN, Palo Alto, CA, USA, Apr 2003

    Google Scholar 

  16. Williamson G, Cellai D, Dobson S, Lero PN (2009) Modelling periodic data dissemination in wireless sensor networks. In: Proceedings of 3rd UKSim European symposium on computer modeling & simulation, Athens, Greece, 25–27 November 2009 pp 499–504

    Google Scholar 

  17. Yacoab MYM (2011) Multiple sink based compressive data aggregation technique for wireless sensor networks. Int J Wirel Mob Netw 3(2):182

    Article  Google Scholar 

  18. Nguyen D, Tran T, Nguyen T, Bose B (2009) Wireless broadcast using network coding. IEEE Trans Veh Technol 58(2):914–925

    Article  Google Scholar 

  19. Zhan C, Xu Y, Wang J, Lee V (2009) Reliable multicast in wireless networks using network coding. In: Proceedings of the 6th international conference on mobile ad hoc and sensor systems (MASS ’09), Macau, China, pp 506–515

    Chapter  Google Scholar 

  20. Kweon K, Ghim H, Hong J, Yoon H (2009) Gradient-Based Energy-Efficient routing from multiple sources to multiple mobile sinks in wireless sensor networks. In: Proceedings of 4th international symposium on wireless pervasive computing (ISWPC)

    Google Scholar 

  21. Kim HS, Abdelzaher TF, Kwon WH (2003) Minimum-energy asynchronous dissemination to mobile sinks in wireless sensor networks. In: Proceedings of the international conference on embedded networked sensor systems (SenSys ’03), pp 193–204

    Chapter  Google Scholar 

  22. Hamida EB, Chelius G (2008) A line-based data dissemination protocol for wireless sensor networks with mobile sink. In: Proceedings of IEEE international conference on communications (ICC’08), Beijing, China, 19–23 May 2008, pp 2201–2205

    Chapter  Google Scholar 

  23. Viana AC, Ziviani A, Friedman R (2009) Decoupling data dissemination from mobile sinks trajectory in wireless sensor networks. IEEE Commun Lett 13:178–180

    Article  Google Scholar 

  24. Wang G, Wang T et al (2009) Adaptive location updates for mobile sinks in wireless sensor networks. J Supercomput 47:127–145

    Article  Google Scholar 

  25. Chen Z, Liu S (2011) Multi-tier grid routing to mobile sink in large-scale wireless sensor networks. J Netw 6(5):765–773

    Google Scholar 

  26. Basagni S, Carosi A et al (2008) Controlled sink mobility for prolonging wireless sensor networks lifetime. Wirel Netw 14:831–858

    Article  Google Scholar 

  27. Dorigo M (1992) Optimization, learning and natural algorithms. PhD dissertation, Politecnico di Milano, Italy (in Italian)

  28. Montemanni R, Gambardella L (2005) Swarm approach for a connectivity problem in wireless networks. In: Proceedings of IEEE swarm intelligence symposium, pp 265–272

    Google Scholar 

  29. Di Caro GA (2004) Ant colony optimization and its application to adaptive routing in telecommunication networks. PhD thesis, Polytechnic School, Université Libre de Bruxelles, Brussels, Belgium

  30. Agassounon W (2003) Distributed information retrieval and dissemination in swarm-based networks of mobile, autonomous agents. In: Proceedings of IEEE swarm intelligence symposium, pp 152–159

    Google Scholar 

  31. Selvakennedy S, Sinnappan S, Shang Y (2006) Data dissemination based on ant swarms for wireless sensor networks. In: Proceedings of 3rd consumer communications and networking conference (CCNC’ 06), Las Vegas, Nevada, USA, 8–10 January 2006, pp 132–136

    Google Scholar 

  32. Dhurandher SK, Misra S, Obaidat MS, Gupta P, Verma K, Narula P (2009) An energy-aware routing protocol for ad-hoc networks based on the foraging behavior in ant swarms. In: Proceedings of IEEE international conference on communication (ICC’09), Dresden, Germany, 14–18 June 2009, pp 1–5

    Chapter  Google Scholar 

  33. Liao WH, Kao Y, Fan C-M (2007) An ant colony algorithm for data aggregation in wireless sensor networks. In: Proceedings of 2007 international conference on sensor technologies and applications (SENSORCOMM’07), Washington, DC, USA. ISBN 0-7695-2988-7

    Google Scholar 

  34. Misra R, Mandal C (2007) Ant-aggregation: ant colony algorithm for optimal data aggregation in wireless sensor networks. In: Proceedings of international conference on sensor technologies and applications (SENSORCOMM ’07), Washington, DC, USA. ISBN 0-7695-2988-7

    Google Scholar 

  35. Das S, Singh G, Pujar S, Koduru P (2006) Ant colony algorithms for routing in sensor networks. In: Proceedings of international conference on artificial intelligence, Las Vegas, NV, pp 457–464

    Google Scholar 

  36. Wang W, Li W, Chen D, Han Y (2009) Ant colony based routing algorithm for multi-sink networks. In: Proceedings of IEEE world congress on computer science and information engine, vol 1, 31 March–2 April 2009

    Google Scholar 

  37. Stutzle T, Hoos H (2000) MAX-MIN ant system. Future Gener Comput Syst 16:889–914

    Article  Google Scholar 

  38. Misra S, Thomasinous PD (2010) A simple, least-time, and energy-efficient routing protocol with one-level data aggregation for wireless sensor networks. J Syst Softw 83(5):852–860

    Article  Google Scholar 

  39. Madden S, Franklin M, Hellerstein J, Hong W (2003) The design of an acquisitional query processor for sensor networks. In: Proceedings of the ACM international conference on management of data (SIGMOD ’03), pp 491–502

    Google Scholar 

  40. Charles D, Fyfe C, McGlinchey L (2007) Biologically inspired artificial intelligence for computer games. IGI, New York. ISBN 9781591406464

    Book  Google Scholar 

  41. Zeng X, Bagrodia R, Gerla M (1998) Glomosim: a library for parallel simulation of large-scale wireless networks. In: Proceedings of the 12th workshop on parallel and distributed simulations (PADS), May 1998, pp 154–161

    Google Scholar 

  42. Bagrodia R, Meyer RA (1998) Parsec user manual. http://pcl.cs.ucla.edu/projects/parsec/manual/ (last visited 2 September 2011)

  43. IEEE computer society LAN MAN standards committee (1997) Wireless LAN medium access protocol (MAC) and physical layer (PHY) specification. IEEE Std. 802.11, The Institute of Electrical and Electronics Engineers, New York

  44. Bellman Ford algorithm. http://xlinux.nist.gov/dads/HTML/bellmanford.html (last visited 30 April 2012)

  45. Burke EK, Bykov Y (2008) A late acceptance strategy in hill-climbing for exam timetabling problems. In: Proceedings of the 7th international conference on the practice and theory of automated timetabling (PATAT 2008), Montreal, QC, Canada, 18–22 August 2008

    Google Scholar 

  46. A* search. http://www.briangrinstead.com/blog/astar-search-algorithm-in-javascript (last visited 30 April 2012)

  47. Engelbrecht AP (2007) Computational intelligence: an introduction, 2nd edn. Wiley, New York. ISBN 978-0-470-03561-0

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Ryerson University, Toronto, ON, Canada

    Isaac Woungang

  2. Division of Information Technology, Netaji Subhas Institute of Technology, University of Delhi, Delhi, India

    Sanjay Kumar Dhurandher

  3. Netaji Subhas Institute of Technology, University of Delhi, Delhi, India

    Lakshaya Agnani & Ankit Mahendru

  4. Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada

    Alagan Anpalagan

Authors
  1. Isaac Woungang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sanjay Kumar Dhurandher
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lakshaya Agnani
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ankit Mahendru
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alagan Anpalagan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Isaac Woungang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Woungang, I., Dhurandher, S.K., Agnani, L. et al. An ant-swarm inspired dynamic multiresolution data dissemination protocol for wireless sensor networks. J Supercomput 65, 524–542 (2013). https://doi.org/10.1007/s11227-012-0804-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-012-0804-8

Keywords

Search

Navigation