Self Organized, Flexible, Latency and Energy Efficient Protocol for Wireless Sensor Networks

  • Sachin Gajjar
  • Mohanchur Sarkar
  • Kankar Dasgupta


This paper presents Self Organized, Flexible, Latency and Energy Efficient (SOFLEE) Protocol, a cross-layer protocol for Wireless Sensor Networks that uses TDMA based medium access scheme combined with multi-hop routing information during time slot allocation. Time slot allocation is done centrally by Master Station (MS) to provide a collision-free and fair media access. MS allocates same transmission slot to nodes that are two hops apart to increase channel spatial reuse and decrease data latency. For data gathering at MS, SOFLEE uses parenthood willingness to forward data to MS through unidirectional tree rooted at MS. Parenthood willingness of a node is decided using: (i) its location with respect to MS, to forward data in correct direction; (ii) its number of children, to prevent local congestion; (iii) its residual energy, to uniformly distribute energy load of being a parent node and (iv) its parent–child communication link reliability to guarantee consistent data delivery. The parenthood willingness requires simple comparisons against thresholds, and thus, is very simple to implement on memory and computationally constrained nodes. Unlike a conventional TDMA-based protocol, SOFLEE provides flexibility to transfer data slots among nodes and priority based slot scheduling to adapt to dynamic traffic patterns of various Wireless Sensor Network applications. Finally, simple, memory and energy efficient techniques for: (i) hop-by-hop congestion control; (ii) catering to orphan nodes, link breakdowns and node deaths are incorporated in SOFLEE. A comparative analysis of SOFLEE, FlexiTP, self organized TDMA protocol, energy efficient fast forwarding and D-MAC show that SOFLEE is 25 to 61 % more energy efficient compared to FlexiTP. Data latency of SOFLEE is 32 to 68 % less, delivery ratio is 7 to 19 %, goodput is 3 % and network lifetime is 253.784 s to 448.440 s more compared to FlexiTP.


Wireless sensor networks Cross-layer protocol Routing Medium access control Congestion control 



The authors thank the anonymous reviewers for their insightful comments and suggestions. This work is in part funded by the Minor Research Program at Institute of Technology, Nirma University, India under contract NU/MR/IT/178 and by Gujarat Council on Science and Technology, Department of Science and Technology, Government of Gujarat, India under contract GUJCOST/MRP/2014-15/424.


  1. 1.
    S. H. Gajjar, S. N. Pradhan and K. S. Dasgupta, Wireless sensor networks: application led research perspective. Proceedings. of IEEE Recent Advances in Intelligent Computational Systems, pp. 025–030, 2011. doi: 10.1109/RAICS.2011.6069266.
  2. 2.
    R. Jurdak, Wireless Ad Hoc and Sensor Networks: A Cross-Layer Design Perspective, SpringerNew York, 2007.Google Scholar
  3. 3.
    T. Melodia, M. C. Vuran and D. Pompili, The State of the Art in Cross-Layer Design for Wireless Sensor Networks. Wireless Systems and Network Architectures Lecture Notes in Computer Science Springer-Verlag Berlin Heidelberg, Vol. 3883: pp. 78–92, 2006. doi: 10.1007/11750673_7.
  4. 4.
    D. P. Lucas, J. Mendes and J. P. C. Rodrigues, A survey on cross-layer solutions for wireless sensor networks, Elsevier Journal of Network and Computer Applications, Vol. 34, No. 2, pp. 523–534, 2011. doi: 10.1016/j.jnca.2010.11.009.CrossRefGoogle Scholar
  5. 5.
    S. H. Gajjar, S. N. Pradhan and K. S. Dasgupta, Cross layer architectural approaches for wireless sensor networks. Proceedings of IEEE Recent Advances in Intelligent Computational Systems, pp. 557–562, 2011. doi: 10.1109/RAICS.2011.6069374.
  6. 6.
    S. Jagadeesan and V. Parthasarathy, Cross-layer design in wireless sensor networks, Advances in Intelligent and Soft Computing, Vol. 166, pp. 283–295, 2012. doi: 10.1007/978-3-642-30157-5_29.CrossRefGoogle Scholar
  7. 7.
    S. Gajjar, S. N. Pradhan and K. S. Dasgupta, Performance analysis of cross layer protocols for wireless sensor networks. Proceedings of International Conference on Advances in Computing, Communication and Informatics, pp. 348–354, 2012. doi: 10.1145/2345396.2345454.
  8. 8.
    W. B. Heinzelman, A. P. Chandrakasan and H. Balakrishnan, An application specific protocol architecture for wireless microsensor networks, IEEE Transactions on Wireless Communications, Vol. 1, No. 4, pp. 660–670, 2002. doi: 10.1109/TWC.2002.804190.CrossRefGoogle Scholar
  9. 9.
    Y. Wang, I. Henning, X. Li and D. Hunter, SOTP: a self-organized TDMA protocol for wireless sensor networks. Proceedings of canadian conference on electrical and computer engineering, pp. 1108–1111, 2006. doi: 10.1109/CCECE.2006.277307.
  10. 10.
    L. Gang, B. Krishnamachari and C. Raghavendra, An adaptive energy-efficient and low-latency MAC for tree-based data gathering in sensor networks, Wiley InterScience Journal of Wireless Communications & Mobile Computing, Vol. 7, pp. 863–875, 2007. doi: 10.1002/wcm.503.CrossRefGoogle Scholar
  11. 11.
    W. L. Lee, A. Datta and R. Cardell-Oliver, FlexiTP: a flexible schedule based TDMA protocol for fault tolerant and energy efficient Wireless Sensor Networks, IEEE Transactions on Parallel and Distributed Systems, Vol. 19, No. 6, pp. 851–864, 2008. doi: 10.1109/TPDS.2007.70774.CrossRefGoogle Scholar
  12. 12.
    K. Pahlavan and A. H. Levesque, Wireless Information Networks, John Wiley & Sons, IncHoboken, 2005.CrossRefGoogle Scholar
  13. 13.
    T. Zhang, L. Chen, D. Chen, L. Xie EEFF: a cross-layer designed energy efficient fast forwarding protocol for wireless sensor networks. Proceedings of IEEE Wireless Communications and Networking Conference, pp. 1–6, 2009. doi: 10.1109/WCNC.2009.4917693.
  14. 14.
    L. Galluccio, A. Leonardi, G. Morabito and S. Palazzo, A MAC/Routing cross-layer approach to geographic forwarding in wireless sensor network, Elsevier Journal of Ad Hoc Networks, Vol. 5, No. 6, pp. 872–884, 2007. doi: 10.1016/j.adhoc.2007.02.004.CrossRefGoogle Scholar
  15. 15.
    P. Casari, M. Nati, C. Petrioli and M. Zorzi, Efficient non planar routing around dead ends in sparse topologies using random forwarding. Proceedings of IEEE International Conference on Communication, pp. 3122–3129, 2007. doi: 10.1109/ICC.2007.518.
  16. 16.
    R. Jurdak. Modeling and Optimization of Ad Hoc and Sensor Networks (2005) Bren School of Information and Computer Science, University of California Irvine. Ph.D. Dissertation.Google Scholar
  17. 17.
    J. Polastre, J. Hill and D. Culler, Versatile low power media access for wireless sensor networks. Proceedings of 2nd International conference on Embedded networked sensor systems, pp. 95–107, 2004. doi: 10.1145/1031495.1031508.
  18. 18.
    C. Suh, Y. B. Ko, D. M. Son (2006) An energy efficient cross-layer MAC protocol for wireless sensor networks. advanced web and network technologies, and applications lecture notes in computer science Springer-Verlag Berlin Heidelberg, Vol. 3842, pp. 410–419. doi: 10.1007/11610496_54.
  19. 19.
    K. Pahlavan and P. Krishnamurthy, Principles of Wireless Networks: A Unified Approach, Prentice Hall PublicationNew Jersey, 2002.Google Scholar
  20. 20.
    Z. Tang and Q. Hu, A cross-layer flooding strategy for wireless sensor networks. Proceedings of 2nd International Conference on Industrial and Information Systems 2, pp. 377–380, 2010. doi: 10.1109/INDUSIS.2010.5565731.
  21. 21.
    M. Iqbal, I. Gondal and L. Dooley, A cross-layer data dissemination protocol for energy efficient sink discovery in wireless sensor networks. Proceedings of IEEE International Conference on Communications, pp. 3455–3462, 2007. doi: 10.1109/ICC.2007.572.
  22. 22.
    S. Liu, K. W. Fan and P. Sinha, CMAC: an energy efficient mac layer protocol using convergent packet forwarding for wireless sensor networks, ACM Transactions on Sensor Networks, Vol. 5, No. 4, p. 29, 2009. doi: 10.1145/1614379.1614381.CrossRefGoogle Scholar
  23. 23.
    S. Cui, R. Madan, A. Goldsmith, S. Lall, Joint routing, MAC, and link layer optimization in sensor networks with energy constraints. Proceedings of IEEE International Conference on Communications 2, pp. 725–729, 2005. doi: 10.1109/ICC.2005.1494448.
  24. 24.
    X. Lin, N. B. Shroff and R. Srikant, A tutorial on cross-layer optimization in wireless networks, IEEE Journal of Selected Areas in Communication, Vol. 24, No. 8, pp. 1452–1463, 2006. doi: 10.1109/JSAC.2006.879351.CrossRefGoogle Scholar
  25. 25.
    X. Lin and N. B. Shroff, The impact of imperfect scheduling on cross-layer congestion control in wireless networks, IEEE/ACM Transactions on Networking, Vol. 14, No. 2, pp. 302–315, 2006. doi: 10.1109/TNET.2006.872546.CrossRefGoogle Scholar
  26. 26.
    Y. P. Hsu and K. T. Feng, Cross-layer routing for congestion control in wireless sensor networks. Proceedings of IEEE Radio and Wireless Symposium, pp. 783–786, 2008. doi: 10.1109/RWS.2008.4463609.
  27. 27.
    N. Chilamkurti, S. Zeadally, A. Vasilakos and V. Sharmal, Cross-layer support for energy efficient routing in wireless sensor networks. Journal of Sensors, Hindawi Publishing Corporation: 9, 2009. doi: 10.1155/2009/134165.
  28. 28.
    J. Broch, D. B. Johnson and D. A. Maltz, The dynamic source routing protocol for mobile ad hoc networks. Accessed 21 July 2014.
  29. 29.
    S. Xu and T. Saadawi, Does the IEEE 802.11 MAC protocol work well in multihop wireless ad hoc networks? Proceedings of IEEE Communication Magazine, Vol. 39, No. 6, pp. 130–137. doi: 10.1109/35.925681.
  30. 30.
    K. Saleem, N. Fisal, S. Hafizah, S. Kamilah, R. Rashid and Y. Baguda, Cross layer based biological inspired self-organized routing protocol for wireless sensor networks. Proceedings of IEEE Region 10 Conference, pp. 1–6, 2009. doi: 10.1109/TENCON.2009.5395945.
  31. 31.
    V. D. Park, M. S. Corson, Temporally-ordered routing algorithm. Accessed 21 July 2014.
  32. 32.
    B. DeCleene, V. Firoiu, M. Dorsch and S. Zabele, Cross-layer protocols for energy-efficient wireless sensor networking. Proceedings of IEEE Military Communications Conference 3, pp. 1477–1484, 2005. doi: 10.1109/MILCOM.2005.1605885.
  33. 33.
    M. Vuran and I. F. Akyildiz, XLP: a cross-layer protocol for efficient communication in WSNs, IEEE Transactions on Mobile Computing, Vol. 9, No. 11, pp. 1578–1591, 2010. doi: 10.1109/TMC.2010.125.CrossRefGoogle Scholar
  34. 34.
    Y. Li and R. Bartos, Energy efficient reactive store-and-forward protocol for intermittently connected networks. Proceedings of IEEE Conference on Global Communications, pp. 563–568, 2013. doi: 10.1109/GLOCOM.2013.6831131.
  35. 35.
    O. Gnawali, R. Fonseca, K. Jamieson, D. Moss and P. Levis, The collection tree protocol. Proceedings of 7th ACM Conference on Embedded Networked Sensor System, pp. 1–14, 2009. doi: 10.1145/1644038.1644040.
  36. 36.
    M. Li, D. Agrawal, D. Ganesan and A. Venkataramani, Block-switched networks: a new paradigm for wireless transport. Proceedings of 6 th ACM/USENIX Symposium on Networked Systems Design and Implementation, pp. 423–436, 2009, Accessed 21 July 2014.
  37. 37.
    M. Hefeida, T. Canli and A. Khokhar, CL-MAC: a cross-layer mac protocol for heterogeneous wireless sensor networks, Elsevier Journal of Ad Hoc Networks, Vol. 11, No. 1, pp. 213–225, 2013. doi: 10.1016/j.adhoc.2012.05.005.CrossRefGoogle Scholar
  38. 38.
    F. Cuomo, A. Abbagnale and E. Cipollone (2013) Cross-layer network formation for energy-efficient IEEE 802.15.4/ZigBee Wireless Sensor Networks, Elsevier Journal of Ad Hoc Networks, Vol. 11, No. 2, pp. 672–686, 2004. doi: 10.1016/j.adhoc.2011.11.006.
  39. 39.
    IEEE Standard for Low-Rate Wireless Personal Area Networks specification. Accessed 21 July 2014.
  40. 40.
    S. Gajjar, N. Choksi, M. Sarkar and K. Dasgupta, Comparative analysis of wireless sensor network motes. Proceedings of International Conference on Signal Processing and Integrated Networks, pp. 426–431, 2014. doi: 10.1109/SPIN.2014.6776991.
  41. 41.
    J. Elson, L. Girod and D. Estrin, Fine-grained network time synchronization using reference broadcasts. Proceedingsof 5 th Symposium on Operating Systems Design and Implementation 36(SI), pp. 147–163, 2002. doi: 10.1145/844128.844143.
  42. 42.
    R. Rajagopalan and P. Varshney, Data aggregation techniques in sensor networks: a survey, IEEE Communications and Surveys and Tutorials, Vol. 8, No. 4, pp. 48–63, 2006. doi: 10.1109/COMST.2006.283821.CrossRefGoogle Scholar
  43. 43.
    The Network Simulator NS-2. Accessed 21 July 2014.
  44. 44.
    S. Gradshteyn, I. M. Ryzhik, A. Jeffrey and D. Zwillinger, Tables of Integrals, Series, and Products, Academic PressNew York, 2000.Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Sachin Gajjar
    • 1
  • Mohanchur Sarkar
    • 2
  • Kankar Dasgupta
    • 3
  1. 1.Department of Computer Science and Engineering, Institute of TechnologyNirma UniversityAhmedabadIndia
  2. 2.SATCOM and Navigation Applications Area, Space Application Centre (SAC)Indian Space Research Organization (ISRO)AhmedabadIndia
  3. 3.Indian Institute of Space Science and TechnologyThiruvananthapuramIndia

Personalised recommendations