Skip to main content
SpringerLink
Log in

Medium Access Control Protocols for Mission Critical Wireless Sensor Networks

  • Chapter
  • First Online:
Handbook of Wireless Sensor Networks: Issues and Challenges in Current Scenario's

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1132))

Abstract

Wireless sensor networks have variety of applications in military and civilian tracking, habitat monitoring, patient monitoring and industrial control and automation. Many protocols have been developed to support these applications. For applications such as gas leakage detection system, volcanic activities alerts, fire safety systems, border surveillance and tsunami alert systems where apart from energy saving, timely information delivery is also important, an efficient MAC protocol is required. These are termed as mission critical applications. Reducing energy consumption, efficient utilization of bandwidth, Throughput, Latency, Scalability and Adaptability, Reliability, and Degree of Intelligence are the most important parameters of a good MAC protocol designed for mission critical applications. The degree of intelligence is the parameter which is novel to these protocols and will be provided by introducing the Machine learning and Artificial Intelligence. The chapter addresses the design issues for MAC layer, different MAC protocols designed for wireless sensor networks, mission Critical Applications of WSNs and the performance parameters required for Mission Critical MAC Protocols. Various MAC protocols based on contention based and contention free channel access mechanism are discussed in detail in the chapter. Now we are in the era, where each application demands intelligence and automation. For this purpose, there is need to design smart protocols adaptive to critical scenarios. In the chapter the existing MAC protocols and the performance parameters for a mission critical MAC protocol such as throughput, packet delivery ratio, packet loss rate, efficient bandwidth utilization, scalability and adaptability are discussed. A review of machine learning techniques is also done which shows that MAC protocols may be enhanced for their suitability in mission critical scenarios. The chapter also discussed the case study of one mission critical MAC protocol and its comparison with SMAC protocol. The application of mission critical MAC protocol in pipeline leakage detection system is also discussed with its design model. Finally the chapter ends with discussion of recent issues and challenges and future scope of intelligent ML based MAC protocol design.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Commun. Mag. 40(8), 102–114 (2002)

    Article  Google Scholar 

  2. Yick, J., Mukherjee, B., Ghosal, D.: Wireless sensor network survey. Comput. Netw. 52(12), 2292–2330 (2008)

    Article  Google Scholar 

  3. Kazem, S., Daniel, M., Taineb, Z.: Wireless Sensor Networks: Technology, Protocols, and Applications. Wiley, Hoboken (2007)

    Google Scholar 

  4. LAN-MAN Standards Committee of the IEEE Computer Society, Wireless LAN medium access control (MAC) and physical layer (PHY) specification. IEEE, New York (1997). (IEEE Std 802.11-1997 edition)

    Google Scholar 

  5. Demirkol, I., Ersoy, C., Alagoz, F.: MAC protocols for wireless sensor networks: a survey. IEEE Commun. Mag. 44(4), 115–121 (2006)

    Article  Google Scholar 

  6. Ye, W., Heidemann, J., Estrin, D.: An energy-efficient MAC protocol for wireless sensor networks. In: Proceedings of the IEEE INFOCOM, New York, NY, vol. 3, pp. 1567–1576, June 2002

    Google Scholar 

  7. Ye, W., Heidemann, J., Estrin, D.: Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Trans. Netw. 12(3), 493–506 (2004)

    Article  Google Scholar 

  8. Ameen, M.A., Islam, S.M.R., Kwak, K.: Energy saving mechanisms for MAC protocols in wireless sensor networks. Int. J. Distrib. Sens. Netw. 6(1), 163413 (2010)

    Article  Google Scholar 

  9. Suriyachai, P., Roedig, U., Scott, A.: A survey of MAC protocols for mission-critical applications in wireless sensor networks. IEEE Commun. Surv. Tutor. 14(2), 240–264 (2012). (Second Quarter)

    Article  Google Scholar 

  10. Karl, H., Willig, A.: Protocols and Architectures for Wireless Sensor Networks. Wiley, Hoboken (2005)

    Book  Google Scholar 

  11. Mishra, S.C., Woungang, I., Mishra, S.: Guide to Wireless Sensor Networks. Springer, London (2009)

    Book  Google Scholar 

  12. Ali, M., Böhm, A., Jonsson, M.: Wireless sensor networks for surveillance applications – a comparative survey of MAC protocols. In: The Fourth International Conference on Wireless and Mobile Communications, Athens, pp. 399–403 (2008)

    Google Scholar 

  13. Stoianov, I., Nachman, L., Madden, S., Tokmouline, T.: PIPENET: a wireless sensor network for pipeline monitoring. In: 6th International Symposium on Information Processing in Sensor Networks, Cambridge, MA, pp. 264–273 (2007)

    Google Scholar 

  14. Casey, K., Lim, A., Dozier, G.: A sensor network architecture for tsunami detection and response. Int. J. Distrib. Sens. Netw. 4(1), 27–42 (2008)

    Article  Google Scholar 

  15. Tan, R., Xing, G., Chen, J., Song, W.Z., Huang, R.: Quality-driven volcanic earthquake detection using wireless sensor networks. In: 2010 31st IEEE Real-Time Systems Symposium, San Diego, CA, pp. 271–280 (2010)

    Google Scholar 

  16. Kumar, S., Raghavan, V.S., Deng, J.: Medium access control protocols for ad hoc wireless networks: a survey. AdHoc Netw. 4(3), 326–358 (2006)

    Google Scholar 

  17. Jamieson, K., Balakrishnan, H., Tay, C.: Sift: a mac protocol for event-driven wireless sensor networks. ESWN 6, 260–275 (2006)

    Google Scholar 

  18. El-Hoiydi, A., Decotignie, J.D.: WiseMAC: an ultra low power MAC protocol for multi-hop wireless sensor networks. In: Algorithmic Aspects of Wireless Sensor Networks (ALGOSENSORS 2004). Lecture Notes in Computer Science, vol. 3121, pp. 81–31. Springer, Berlin (2004)

    Chapter  Google Scholar 

  19. Lu, G., Krishnamachari, B., Raghavendra, C.S.: An adaptive energy-efficient and low-latency MAC for data gathering in wireless sensor networks. In: Proceedings of the 18th International Parallel and Distributed Processing Symposium, p. 224, April 2004

    Google Scholar 

  20. Li, Y., Ye, W., Heidemann, J.: Energy and latency control in low duty cycle MAC protocols. In: Proceedings of IEEE Wireless Communications and Networking Conference, New Orleans, LA, USA, vol. 2, pp. 676–682 (2005)

    Google Scholar 

  21. Hussain, S.W., Khan, T., Zaidi, S.M.H.: Latency and energy efficient MAC (LEEMAC) protocol for event critical applications in WSNs. In: Proceedings of International Symposium on Collaborative Technologies and Systems, Las Vegas, NV, USA, pp. 370–378 (2006)

    Google Scholar 

  22. Dam, T.V., Langendoen, K.: An adaptive energy-efficient MAC protocol for wireless sensor networks. In: The First ACM Conference on Embedded Networked Sensor Systems (Sensys 2003), Los Angeles, CA, USA, pp. 171–180, November 2003

    Google Scholar 

  23. Rajendran, V., Obraczka, K., Aceves, J.J.: Energy efficient, collision-free medium access control for wireless sensor networks. In: Proceedings of ACM (SenSys 2003), Los Angeles, California, pp. 181–192, November 2003

    Google Scholar 

  24. Lin, P., Qiao, C., Wang, X.: Medium access control with a dynamic duty cycle for sensor networks. In: IEEE Wireless Communications and Networking Conference, vol. 3, pp. 1534–1539, 21–25 March 2004

    Google Scholar 

  25. Ezzedine, T., Miladi, M., Bouallegue, R.: An energy-latency-efficient MAC protocol for wireless sensor networks. Int. J. Electr. Comput. Eng. 4(13), 816–821 (2009)

    Google Scholar 

  26. Tseng, H.W., Yang, S.H., Chuang, P.Y., Wu, H.K., Chen, G.H.: An energy consumption analytic model for a wireless sensor MAC protocol. In: Proceedings of the IEEE Vehicular Technology Conference (VTC 2004), pp. 4533–4537 (2004)

    Google Scholar 

  27. Hamady, F., Sabra, M., Sabra, Z., Kayssi, A., Chehab, A., Mansour, M.: Enhancement of the S-MAC protocol for wireless sensor networks. In: 2010 International Conference on Energy Aware Computing, Cairo, pp. 1–4 (2010)

    Google Scholar 

  28. Ammar, I., Awan, I., Min, G.: An improved S-MAC protocol based on parallel transmission for wireless sensor networks. In: Proceedings of 13th International Conference on Network-Based Information Systems (NBIS 2010), pp. 48–54. IEEE Computer Society, Washington (2010)

    Google Scholar 

  29. Xia, F., Zhao, W., Sun, Y., Tian, Y.C.: Fuzzy logic control based QoS management in wireless sensor/actuator networks. Sensors 7, 3179–3191 (2007). (Basel Switzerland)

    Article  Google Scholar 

  30. Yusuf, M., Haider, T.: Energy-aware fuzzy routing for wireless sensor networks. In: Proceedings of the IEEE Symposium on Emerging Technologies, pp. 63–69 (2005)

    Google Scholar 

  31. Misra, S., Mohanta, D.: Adaptive listen for energy-efficient medium access control in wireless sensor networks. J. Multimed. Tools Appl. 47(1), 121–145 (2010)

    Article  Google Scholar 

  32. Mishra, C.K., Acharya, B.M., Das, K., Pati, P.S.: EX-SMAC: an adaptive low latency energy efficient MAC protocol. Int. J. Comput. Sci. Eng. IJCSE 3(4), 1485–1489 (2011)

    Google Scholar 

  33. Ramakrishnan, S., Mullen, J.: Impact of sleep in wireless sensor MAC protocol. In: Vehicular Technology Conference, VTC2004-Fall. IEEE 60th Conference, vol. 7 (2004)

    Google Scholar 

  34. Ramchand, V., Lobiyal, D.K.: An analytical model for power control T-MAC protocol. Int. J. Comput. Appl. 12(1), 975–8887 (2010)

    Google Scholar 

  35. Arisha, K.A., Youssef, M.A., Younis, M.F.: Energy aware TDMA based MAC for sensor network. In: IEEE Workshop on Integrated Management of Power Aware Communications Computing and Networking (2002)

    Google Scholar 

  36. Barroso, A., Roedig, U., Sreenan, C.: μ-MAC: an energy efficient medium access control for wireless sensor networks. In: Proceedings of the Second European Workshop on Wireless Sensor Networks, pp. 70–80 (2005)

    Google Scholar 

  37. Campelli, L., Capone, A., Cesana, M., Ekici, E.: A receiver oriented MAC protocol for wireless sensor networks. In: Proceedings of IEEE MASS 2007, pp. 1–10, 8–11 October 2007

    Google Scholar 

  38. Rhee, I., Warrier, A., Aia, M., Min, J.: ZMAC: a hybrid MAC for wireless sensor networks. In: Proceedings of the Third ACM Conference on Embedded Networked Sensor System (Sensys 2005), pp. 90–101 (2005)

    Google Scholar 

  39. Hamid, M.A., Wadud, M., Chong, I.: A schedule-based multi-channel MAC protocol for wireless sensor networks. Sensors 10, 9466–9480 (2010)

    Article  Google Scholar 

  40. Zhou, G., Huang, C., Yan, T., He, T., Stankovic, J.A., Abdelzaher, T.F.: MMSN: multi-frequency media access control for wireless sensor networks. In: Proceedings of IEEE INFOCOM, 25TH IEEE International Conference on Computer Communications, Barcelona, Spain, pp. 1–13 (2006)

    Google Scholar 

  41. Incel, O.D., Dulman, S., Jansen, P.: Multi-channel Support for dense wireless sensor networking. In: EUROSSC, LNCS, vol. 4272, pp. 1–14 (2006)

    Google Scholar 

  42. Chen, X., Han, P., He, Q.S., Tu, S.L., Chen, Z.L.: A multi-channel MAC protocol for wireless sensor networks. In: The Sixth IEEE International Conference on Computer and Information Technology (CIT 2006), Seoul, p. 224 (2006)

    Google Scholar 

  43. Incel, O.D., Jansen, P.G., Mullender, S.J.: MC-LMAC: a multi-channel mac protocol for wireless sensor networks. Technical Report TR-CTIT-08-61, Centre for Telematics and Information Technology, University of Twente, Enschede (2008)

    Google Scholar 

  44. Du, S., Saha, A.K., Johnson, D.B.: RMAC: a routing-enhanced duty-cycle MAC protocol for wireless sensor networks. In: Proceedings of the 26th IEEE International Conference on Computer Communications, pp. 1478–1486 (2007)

    Google Scholar 

  45. Cho, K.T., Bahk, S.: Optimal hop extended MAC protocol for wireless sensor networks. Comput. Netw. 56, 1458–1469 (2012)

    Article  Google Scholar 

  46. SCADDS: Scalable Coordination Architectures for Deeply Distributed Systems web page. http://www.isi.edu/scadds/projects/smac/

  47. The Network Simulator - ns-2 homepage. http://www.isi.edu/nsnam/ns/

  48. The VINT project. The NS Manual. UC Berkeley, LBL, USC/ISI, and Xerox PARC. http://www.isi.edu/nsnam/ns/doc/ns_doc.pdf

  49. Greis, M.: Tutorial for the network simulator ns. http://www.isi.edu/nsnam/ns/tutorial/index.html

  50. Smac-users – Discussions by users of S-MAC web page. http://mailman.isi.edu/mailman/listinfo/smac-users

  51. Energy Model Update in ns-2 web page. http://www.isi.edu/ilense/software/smac/ns2_energy.html

  52. http://www.isi.edu/nsnam/ns/

  53. Alotaibi, B., Elleithy, K.: A new MAC address spoofing detection technique based on random forests. Sensors 16(3), 1–14 (2016)

    Article  Google Scholar 

  54. Habib, C., Makhoul, A., Darazi, R., Salim, C.: Self-adaptive data collection and fusion for health monitoring based on body sensor networks. IEEE Trans. Ind. Inf. 12(6), 2342–2352 (2016)

    Article  Google Scholar 

  55. Pérez-Solano, J.J., Felici-Castell, S.: Adaptive time window linear regression algorithm for accurate time synchronization in wireless sensor networks. Ad Hoc Netw. 24, 92–108 (2015)

    Article  Google Scholar 

  56. Rezaee, A.A., Pasandideh, F.: A fuzzy congestion control protocol based on active queue management in wireless sensor networks with medical applications. Wirel. Pers. Commun. 98(1), 815–842 (2018)

    Article  Google Scholar 

  57. Sharma, A., Kakkar, A.: Forecasting daily global solar irradiance generation using machine learning. Renew. Sustain. Energy Rev. 82(P3), 2254–2269 (2018)

    Article  Google Scholar 

  58. Sakya, G., Sharma, V.: ADMC-MAC: energy efficient adaptive MAC protocol for mission critical applications in WSN. Sustain. Comput. Inform. Syst. 23, 21–28 (2019). https://doi.org/10.1016/j.suscom.2019.05.001. (ISSN 2210-5379)

    Article  Google Scholar 

  59. Vining, G.G., Peck, E.A., Montgomery, D.C.: Introduction to Linear Regression Analysis, vol. 821. Wiley, Hoboken (2012)

    MATH  Google Scholar 

  60. Sun, W., Yuan, X., Wang, J., Li, Q., Chen, L., Mu, D.: End-to-end data delivery reliability model for estimating and optimizing the link quality of industrial WSNs. IEEE Trans. Autom. Sci. Eng. 15, 1127–1137 (2017)

    Article  Google Scholar 

  61. Song, X., Wang, C., Gao, J., Hu, X.: DLRDG: distributed linear regression-based hierarchical data gathering framework in wireless sensor network. Neural Comput. Appl. 23(7–8), 1999–2013 (2013)

    Article  Google Scholar 

  62. He, H., Zhu, Z., Mäkinen, E.: Task-oriented distributed data fusion in autonomous wireless sensor networks. Soft. Comput. 19(8), 2305–2319 (2015)

    Article  Google Scholar 

  63. Belgiu, M., Drăguţ, L.: Random forest in remote sensing: a review of applications and future directions. ISPRS J. Photogramm. Remote Sens. 114, 24–31 (2016)

    Article  Google Scholar 

  64. Elghazel, W.: Wireless sensor networks for Industrial health assessment based on a random forest approach. Automatic. Université de Franche-Comté (2015). (English. NNT: 2015BESA2055. tel01725629)

    Google Scholar 

  65. Alrajeh, N.A., Khan, S., Mauri, J.L., Loo, J.: Artificial neural network based detection of energy exhaustion attacks in wireless sensor networks capable of energy harvesting. Ad Hoc Sens. Wirel. Netw. 22(1–2), 109–133 (2014)

    Google Scholar 

  66. Shu, J., Liu, S., Liu, L., Zhan, L., Hu, G.: Research on link quality estimation mechanism for wireless sensor networks based on support vector machine. Chin. J. Electron. 26(2), 377–384 (2017)

    Article  Google Scholar 

  67. Gholipour, M., Haghighat, A.T., Meybodi, M.R.: Hop-by-hop congestion avoidance in wireless sensor networks based on genetic support vector machine. Neurocomputing 223, 63–76 (2017)

    Article  Google Scholar 

  68. Kumar, D.P., Amgoth, T., Annavarapu, C.S.R.: Machine learning algorithms for wireless sensor networks: a survey. Inf. Fusion 49, 1–25 (2019)

    Article  Google Scholar 

  69. Sakya, G., Sharma, V.: MAC protocol with regression based dynamic duty cycle feature for mission critical applications in WSN. Int. J. Adv. Comput. Sci. Appl. 8(6), 198–206 (2017). (E-SCI, Thomson Reuters, Web of Science)

    Google Scholar 

  70. Singh, P., Paprzycki, M., Bhargava, B., Chhabra, J., Kaushal, N., Kumar, Y. (eds.): FTNCT 2018. Communications in Computer and Information Science, vol. 958. Springer, Singapore (2018)

    Google Scholar 

  71. Sun, Y., Peng, M., Zhou, Y., Huang, Y., Mao, S.: Application of machine learning in wireless networks: key techniques and open issues. IEEE Commun. Surv. Tutor. 21, 3072–3108 (2019)

    Article  Google Scholar 

Download references

Acknowledgement

This research is funded by AKTU Lucknow (U.P.) as award of grant under “Collaborative Research Innovation Program (CRIP) funding through TEQUIP-III of AKTU” 2019-20. The reference number of grant is AKTU/Dean-PGSR/2019/CRIP/44.

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, JSS Academy of Technical Education, Noida, UP, India

    Gayatri Sakya

  2. Department of Computer Science and Engineering, Jaypee University of Information Technology, Waknaghat, Solan, HP, India

    Pradeep Kumar Singh

Authors
  1. Gayatri Sakya
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pradeep Kumar Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pradeep Kumar Singh .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Jaypee University of Information Technology, Kandaghat, India

    Pradeep Kumar Singh

  2. Department of Computer Sciences, Purdue University, West Lafayette, IN, USA

    Bharat K. Bhargava

  3. Polish Academy of Sciences, Systems Research Institute, Warszawa, Poland

    Marcin Paprzycki

  4. Department of Computer Science and Engineering, National Institute of Technology, Delhi, India

    Narottam Chand Kaushal

  5. School of Education Intelligent Technology, Jiangsu Normal University, Xuzhou, Jiangsu, China

    Wei-Chiang Hong

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Sakya, G., Singh, P.K. (2020). Medium Access Control Protocols for Mission Critical Wireless Sensor Networks. In: Singh, P., Bhargava, B., Paprzycki, M., Kaushal, N., Hong, WC. (eds) Handbook of Wireless Sensor Networks: Issues and Challenges in Current Scenario's. Advances in Intelligent Systems and Computing, vol 1132. Springer, Cham. https://doi.org/10.1007/978-3-030-40305-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-40305-8_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-40304-1

  • Online ISBN: 978-3-030-40305-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation