, Volume 97, Issue 3, pp 205–236 | Cite as

LINKORD: link ordering-based data gathering protocol for wireless sensor networks

  • Marjan Radi
  • Behnam Dezfouli
  • Kamalrulnizam Abu Bakar
  • Shukor Abd Razak
  • Malrey Lee


With respect to the multi-hop communication pattern of wireless sensor networks, all the nodes should establish multi-hop paths towards a common data gathering point to provide a data gathering service for the underlying applications. Although data gathering protocols provide a simple service, these protocols suffer from poor performance in practice due to the power constraints of low-power sensor nodes and unreliability of wireless links. Existing data gathering protocols rely on the ETX metric to find high-throughput paths through assuming there is an infinite number of transmission attempts at the link layer for delivering a single packet over every link. However, in practice the link layer provides a bounded number of transmissions per packet over individual links. Therefore, employing existing data gathering protocols in these situations may result in the construction of the paths that require more than maximum number of provided link layer transmissions for delivering a single packet over each link. In this regard, we propose a path cost function which considers the limitation on the number of provided link layer transmissions and relative position of the links along the paths according to their data transmission probability. Furthermore, we introduce a data gathering protocol which uses the proposed path cost function to construct high-throughput paths. Moreover, this protocol employs a newly designed congestion control mechanism during the data transmission process to provide energy-efficient and high-throughput data delivery. The simulation results show that, the proposed protocol improves data delivery ratio by 70 % and network goodput by 80 %, while it reduces the consumed energy for data delivery by 50 % compared to the default data gathering protocol of TinyOS.


Wireless sensor networks Data gathering Link ordering  Link quality Energy-efficiency 

Mathematics Subject Classification

68M10 68M12 90B18 


  1. 1.
    Arampatzis T, Lygeros J, Manesis S (2005) A survey of applications of wireless sensors and wireless sensor networks. In: Proceedings of the 2005 IEEE international symposium on, mediterrean conference on control and automation intelligent control, 2005, IEEE, pp 719–724Google Scholar
  2. 2.
    Baccour N, Jamaa MB (2009) A comparative simulation study of link quality estimators in wireless sensor networks. In: IEEE international symposium on modeling, analysis & simulation of computer and telecommunication systems (MASCOTS ’09), pp 1–10Google Scholar
  3. 3.
    Baccour N, Mottola L, Niga MZ (2012) Radio link quality estimation in wireless sensor networks : a survey. ACM Trans Sens Netw 8(4):35CrossRefGoogle Scholar
  4. 4.
    Borges VC, Curado M, Monteiro E (2011) Cross-layer routing metrics for mesh networks: current status and research directions. Comput Commun 34(6):681–703CrossRefGoogle Scholar
  5. 5.
    Burri N, Rickenbach PV (2007) Dozer: ultra-low power data gathering in sensor networks. In: Proceedings of the 6th international conference on information processing in sensor networks (IPSN ’07), pp 450–459Google Scholar
  6. 6.
    Cerpa A, Wong JL, Potkonjak M, Estrin D (2005) Temporal properties of low power wireless links: modeling and implications on multi-hop routing. In: Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing (MobiHoc ’05)Google Scholar
  7. 7.
    Colesanti U, Santini S (2011) The collection tree protocol for the castalia wireless sensor networks simulator. Tech. rep., No 729, Department of Computer Science, ETH Zurich, Zurich, SwitzerlandGoogle Scholar
  8. 8.
    Couto DSJD, Aguayo D, Bicket J, Morris R (2003) A high-throughput path metric for multi-hop wireless routing. ACM Mobicom Conf. ACM, San Diego, pp 134–146Google Scholar
  9. 9.
    Das S, Pucha H, Papagiannaki K (2007) Studying wireless routing link metric dynamics. In: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement (IMC ’07), pp 327–332Google Scholar
  10. 10.
    Deshpande V, Sarode P, Sarode S (2010) Root cause analysis of congestion in wireless sensor network. Int J Comput Appl 1(18):31–34Google Scholar
  11. 11.
    Dezfouli B, Radi M, Razak SA, Whitehouse K, Bakar KA, Hwee-pink T (2014) Improving broadcast reliability for neighbor discovery, link estimation and collection tree construction in wireless sensor networks. Comp Netw 62:101–121Google Scholar
  12. 12.
    Dezfouli B, Radi M, Razak SA, Bakar KA, Hwee-pink T (2014) Modeling low-power wireless communications. J Comp Netw Appl 1–31. doi: 10.1016/j.jnca.2014.02.009
  13. 13.
    Draves R, Zill B, Padhye J (2004) Comparison of routing metrics for static multi-hop wireless networks. In: Proceedings of the 2004 conference on applications, technologies, architectures, and protocols for computer communications, ACM, pp 133–144Google Scholar
  14. 14.
    England D, Veeravalli B (2007) A robust spanning tree topology for data collection and dissemination in distributed environments. IEEE Trans Parallel Distrib 18(5):608–620CrossRefGoogle Scholar
  15. 15.
    Ww Fang, Jm Chen, Ts Chu, Dp Qian (2009) Congestion avoidance, detection and alleviation in wireless sensor networks. J Zhejiang Univ Sci C 11(1):63–73Google Scholar
  16. 16.
    Fonseca R, Gnawali O, Jamieson K, Kim S, Levis P, Woo A (2006) The collection tree protocol (CTP). Tech. rep., TEP 123, TinyOS Network Working GroupGoogle Scholar
  17. 17.
    Ganesan D, Krishnamachari B, Woo A, Culler D (2002) Complex behavior at scale: an experimental study of low-power wireless sensor networks. Tech. rep., UCLA/CSD-TR 02–0013, Computer Science Department, UCLAGoogle Scholar
  18. 18.
    García-hernández CF, Ibargüengoytia-gonzález PH, García-hernández J, Pérez-díaz JA (2007) Wireless sensor networks and applications: a survey. Int J Comput Sci Netw Secur 7(3):264–273Google Scholar
  19. 19.
    Gilbert EEPK, Baskaran K (2012) Research issues in wireless sensor network applications: a survey. Int J Inf Electron Eng 2(5):702–706Google Scholar
  20. 20.
    Gnawali O, Jamieson K, Levis P, Fonseca R (2007) Four-bit wireless link estimation. In. In Proceedings of the 6th workshop on hot topics in networks (HotNets ’06), In sixth workshop on hot topics in networks (HotNets)Google Scholar
  21. 21.
    Gnawali O, Fonseca R, Jamieson K (2009) Collection tree protocol. In: Proceedings of the 7th ACM conference on embedded networked sensor systems (SenSys ’09)Google Scholar
  22. 22.
    Heidemann J, Estrin D (2007) Centralized routing for resource-constrained wireless sensor networks. Tech. Rep , August, UCLA, Los Angeles, CA, USAGoogle Scholar
  23. 23.
    Jakllari G, Eidenbenz S (2012) Link positions matter : a noncommutative routing metric for wireless mesh networks. IEEE Trans Mobile Comput 11(1):61–72CrossRefGoogle Scholar
  24. 24.
    Kim KH, Shin KG (2006) On accurate measurement of link quality in multi-hop wireless mesh networks. In: Proceedings of the 12th annual international conference on mobile computing and networking (MobiCom ’06), ACM Press, pp 38–49Google Scholar
  25. 25.
    Levis P, Patel N, Culler D, Shenker S (2004) Trickle: a self-regulating algorithm for code propagation and maintenance in wireless sensor networks. In: Proceddings of the first symposium on networked system design and implementation (NSDI ’04), San Francisco, CAGoogle Scholar
  26. 26.
    Lin S, Zhou G, Whitehouse K, Wu Y (2009) Towards stable network performance in wireless sensor networks. In: Proceedings of the 30th IEEE real-time systems symposium (RTSS ’09), pp 227–237Google Scholar
  27. 27.
    Meier A, Rein T, Beutel J, Thiele L (2008) Coping with unreliable channels: efficient link estimation for low-power wireless sensor networks. In: Proceedings of the 5th international conference on networked sensing systems, IEEE, pp 19–26Google Scholar
  28. 28.
    Moeller S, Sridharan A, Krishnamachari B (2010) Routing without routes: the backpressure collection protocol. In: Proceedings of the 9th ACM/IEEE international conference on information processing in sensor networks (IPSN ’10). Stockholm, Sweden, pp 279–290Google Scholar
  29. 29.
    Polastre J, Hill J, Culler D (2004) Versatile low power media access for wireless sensor networks categories and subject descriptors. In: Proceedings of the 2nd international conference on Embedded networked sensor systems (SenSys ’04). Maryland, USA, pp 95–107Google Scholar
  30. 30.
    Puccinelli D, Haenggi M (2008) Duchy: double cost field hybrid link estimation for low-power wireless sensor networks. In: Proceedings of the 5th workshop on embedded networked sensors (HotEmNets’08)Google Scholar
  31. 31.
    Radi M, Dezfouli B, Nematbakhsh MA (2011) Interference-aware multipath routing protocol for qos improvement in event-driven wireless sensor networks. Tsinghua Sci Technol 16(5):475–490CrossRefGoogle Scholar
  32. 32.
    Radi M, Dezfouli B, Bakar K, Lee M (2012) Multipath routing in wireless sensor networks: survey and research challenges. Sensors 12(1):650–685CrossRefGoogle Scholar
  33. 33.
    Radi M, Dezfouli B, Bakar KA, Razak SA, Lee M (2013) Network initialization in low-power wireless networks: a comprehensive study. Comp J. doi: 10.1093/comjnl/bxt074
  34. 34.
    Radi M, Dezfouli B, Bakar KA, Razak SA (2014) Integration and analysis of neighbor discovery and link quality estimation in wireless sensor networks. Sci World J 2014:1–23. Art No 789642. doi: 10.1155/2014/789642
  35. 35.
    Radi M, Dezfouli B, Bakar KA, Razak SA, Hwee-pink T (2014) IM2PR: interference-minimized multipath routing protocol for wireless sensor. Wirel Netw 1–17. doi: 10.1007/s11276-014-0710-5
  36. 36.
    Schoellhammer T, Greenstein B (2006) Hyper: a routing protocol to support mobile users of sensor networks. Tech report, Center for Embedded Network Sensing (CENS)Google Scholar
  37. 37.
    Srinivasan K, Levis P (2006) RSSI is under appreciated. In: Proceedings of the 3th ACM workshop on embedded networked sensors (EmNets ’06)Google Scholar
  38. 38.
    Srinivasan K, Dutta P, Tavakoli A (2010) An empirical study of low power wireless. ACM Trans Sens Netw 6(2):1–49CrossRefGoogle Scholar
  39. 39.
    TinyOS Network working group (2009) The multihopLQI protocol.
  40. 40.
    Vlavianos A, Law LK, Broustis I, Krishnamurthy SV, Faloutsos M, Kong L (2008) Assessing link quality in IEEE 802.11 Wireless networks: which is the right metric? In: IEEE 19th international symposium on personal. indoor and mobile radio communications, IEEE, pp 1–6Google Scholar
  41. 41.
    Voigt T, Willig A, Kay R, Boano CA, Z MA (2010) The triangle metric : fast link quality estimation for mobile wireless sensor networks. In: Proceedings of 19th international conference on computer communications and networks (ICCCN’10), pp 1–7Google Scholar
  42. 42.
    Wang F, Liu J (2011) Networked wireless sensor data collection: issues, challenges, and approaches. IEEE Commun Surv Tutor 13(4):673–687CrossRefGoogle Scholar
  43. 43.
    Whitehouse K, Woo A, Jiang F, Polastre J, Culler D (2005) Exploiting the capture effect for collision detection and recovery. The second IEEE workshop on embedded networked sensors, 2005. EmNetS-II, IEEE, Sydney, pp 45–52CrossRefGoogle Scholar
  44. 44.
    Woo A, Tong T, Culler D (2003) Taming the underlying challenges of reliable multihop routing in sensor networks. Proceedings of the 1st international conference on Embedded networked sensor systems. ACM, Los Angeles, pp 14–27CrossRefGoogle Scholar
  45. 45.
    Yick J, Mukherjee B, Ghosal D (2008) Wireless sensor network survey. Comput Netw 52(12):2292–2330CrossRefGoogle Scholar
  46. 46.
    Zamalloa MZn, Krishnamachari B (2007) An analysis of unreliability and asymmetry in low-power wireless links. ACM Trans Sens Netw 3(2):34CrossRefGoogle Scholar
  47. 47.
    Zhou G, He T, Krishnamurthy S (2006) Models and solutions for radio irregularity in wireless sensor networks. ACM Trans Sens Netw 2(2):221–262CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  • Marjan Radi
    • 1
  • Behnam Dezfouli
    • 1
  • Kamalrulnizam Abu Bakar
    • 1
  • Shukor Abd Razak
    • 1
  • Malrey Lee
    • 2
  1. 1.Department of Computer Science, Faculty of ComputingUniversiti Teknologi MalaysiaJohor Malaysia
  2. 2.Center for Advanced Image and Information Technology, School of Electronics and Information EngineeringChonBuk National UniversityChonBuk Korea

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