Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

SpringerLink
Log in

On MAC optimization for large-scale wireless sensor network

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

The media access control (MAC) performance of a large-scale wireless sensor network (L-WSN) determines the efficiency of the wireless communication channel. A good MAC protocol could reduce network energy consumption and network delay, which are two problems to be solved urgently in L-WSN. In this paper, we proposed a multi-level integrated MAC protocol (MI-MAC) to solve the overall performance optimization problem of L-WSN. Compared with other protocols, MI-MAC has two mainly improved performances: (1) It improved binary exponential backoff algorithm by twice back off strategy; (2) It designed a sending and receiving algorithm based on the threshold value to recognize control frames (small frames), which effectively avoids the collision probability of data frame. The simulation results show that the MI-MAC protocol improves network throughput and delay performance, significantly reduces energy consumption, and obtains overall network optimization.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

References

  1. Haenggi, M., Andrews, J., Baccetti, F., et al. (2009). Stochastic geometry and random graphs for the analysis and design of wireless networks. IEEE Journal on Selected Areas in Communications, 27(7), 1029–1046.

    Article  Google Scholar 

  2. Gupta, P., & Kumar, P. R. (2000). The capacity of wireless networks. IEEE Transactions on Information Theory, 46(2), 388–404.

    Article  MathSciNet  MATH  Google Scholar 

  3. Wang, X., et al. (2012). A survey of green mobile networks, opportunities and challenges. Mobile Networks and Applications, 17(1), 4–20.

    Article  Google Scholar 

  4. Demirkol, I., Ersoy, C., & Alagoz, F. (2006). MAC protocols for wireless sensor networks, a survey. IEEE Communications Magazine, 44(4), 115–121.

    Article  Google Scholar 

  5. Ye, W., Heidemann, J., & Estrin, D. (2004). Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Transactions on Networking, 12(3), 493–506.

    Article  Google Scholar 

  6. Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the IEEE international conference on computer communications. IEEE INFOCOM ‘02 (Vol. 3, pp. 1567–1576).

  7. Khaled, A., Youssef, M., & Younis, M. (2002). Energy-aware TDMA-based MAC for sensor networks. System-Level Power Optimization for Wireless Multimedia Communication, 43(5), 21–40.

    Google Scholar 

  8. Yoo, D. S., Park, S. S., Choi, S. S., & Park, S. H. (2008). Dynamic S-MAC protocol for wireless sensor networks based on network traffic states. In 14th Asia-Pacific conference on communications. IEEE APCC 2008.

  9. Zheng, T., Radhakrishnan, S., & Sarangan, V. (2005). PMAC: An adaptive energy-efficient mac protocol for wireless sensor networks. In Proceedings of the 19th IEEE international parallel and distributed processing symposium (IPDPS’05)—Workshop 12 (pp. 65–72).

  10. Rajendran, V., Garcia-Luna-Aceves, J. J., & Obraczka, K. (2005). Energy-efficient application-aware medium access for sensor networks. In Conference: Mobile adhoc and sensor systems (pp. 1–10).

  11. Sourabi, K., Gao, J., & Ailawadni, V. (2000). Protocols for self-organization of a wireless sensor network. IEEE Personal Communications, 7(05), 16–27.

    Article  Google Scholar 

  12. Gong, H., Tiu, M., Mao, Y., Chen, T, & Xie, T. (2005). Traffic adaptive MAC protocol for wireless sensor network. In Networking and mobile computing, lecture notes in computer science (Vol. 3619, pp. 1134–1143).

  13. Ding, Y., Sun, Y., & Li, T. (2008). Medium access control protocol for wireless sensor cluster network based on techniques of time division and frequency division. Journal of Tianjin University, 41(8), 904–910.

    Google Scholar 

  14. Rajendran, V., Obraczka, K., & Garcia-Tuna-Aceves, J. J. (2006). Energy-efficient, collision-free medium access control for wireless sensor networks. Wireless Networks, 12(1), 63–78.

    Article  Google Scholar 

  15. Khalil, I. M., Gadallah, Y., Hayajneh, M., & Khreishah, A. (2012). An adaptive OFDMA-based MAC protocol for underwater acoustic wireless sensor networks. Sensors, 12(7), 782–805.

    Google Scholar 

  16. Tong, F., Xie, R., Shu, L., & Kim, Y.-C. (2011). A cross-layer duty cycle MAC protocol supporting a pipeline feature for wireless sensor networks. Sensors, 11(5), 5183–5201.

    Article  Google Scholar 

  17. Ekbatanifard, G., Monsefi, R., Yaghmaee, M. H., & Hosseini, S. A. (2012). Queen-MAC, A quorum-based energy-efficient medium access control protocol for wireless sensor networks. Computer Networks, 56, 2221–2236.

    Article  Google Scholar 

  18. Xiao, Y., et al. (2012). Tight performance bounds of multihop fair access for MAC protocols in wireless sensor networks and underwater sensor networks. IEEE Transactions on Mobile Computing, 11(10), 1538–1554.

    Article  Google Scholar 

  19. Yan, L. S., Pan, W., Luo, B., Li, X. Y., & Liu, J. T. (2011). Modified energy-efficient protocol for wireless sensor networks in the presence of distributed optical fiber senor link. IEEE Sensors, 11(9), 1815–1819.

    Article  Google Scholar 

  20. Blekas, K., & Lagaris, I. E. (2007). Newtonian clustering, an approach based on molecular dynamics and global optimization. Pattern Recognition, 40(6), 1734–1744.

    Article  MATH  Google Scholar 

  21. Li, M., et al. (2013). A survey on topology control in wireless sensor networks, taxonomy, comparative study, and open issues. Proceedings of the IEEE, 101(12), 2538–2557.

    Article  Google Scholar 

  22. Zeng, Y., et al. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.

    Article  Google Scholar 

  23. Camillòa, A., Natic, M., Petriolia, C., & Zorzib, M. (2013). IRIS, integrated data gathering and interest dissemination system for wireless sensor networks. Ad Hoc Networks, 11(2), 654–671.

    Article  Google Scholar 

  24. Liu, X.-Y., Zhu, Y., Kong, L., Liu, C., Gu, Y., Vasilakos, A. V., & Wu, M.-Y. (2015). CDC, compressive data collection for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 26(8), 2188–2197.

    Article  Google Scholar 

  25. Yao, Y., Cao, Q., & Vasilakos, A. V. (2015). EDAL, an energy-efficient, delay-aware, and lifetime-balancing data collection protocol for heterogeneous wireless sensor networks. IEEE/ACM Transactions on Networking, 23(3), 810–823.

    Article  Google Scholar 

  26. Yao, Y., Cao, Q., & Vasilakos, A. V. (2013). EDAL, an energy-efficient, delay-aware, and lifetime-balancing data collection protocol for wireless sensor networks. In 2013 IEEE 10th international conference on mobile ad-hoc and sensor systems (MASS) (pp. 182–190).

  27. Peng, X.-H., & Gu, X. (2006). Co-operative diversity based on distributed coding schemes in wireless networks. BT Technology Journal, 24(2), 97–102.

    Article  Google Scholar 

  28. Wang, G., Zhang, Y., & Amin, M. G. (2007). Space-time cooperation diversity using high-rate codes. Wireless Personal Communications, 43(2), 313–326.

    Article  Google Scholar 

  29. Latré, B., Mil, P. D., Moerman, I., Dhoedt, B., & Demeester, P. (2006). Throughput and delay analysis of unslotted IEEE 802.15.4. Journal of Networks, 1(1), 20–28.

    Article  Google Scholar 

  30. Xiang, L., Luo, J., & Vasilakos, A. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In Proceeding of the 8th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks, Salt Lake City, UT, USA, 27–30 June 2011 (pp. 46–54).

  31. Xu, X., Ansari, R., Khokhar, A., & Vasilakos, A. V. (2015). Hierarchical data aggregation using compressive sensing (HDACS) in WSNs. ACM Transactions on Sensor Networks, 11(3), 45–60.

    Article  Google Scholar 

  32. He, Y., Sun, J., Ma, X., Vasilakos, A. V., Yuan, R., & Gong, W. (2013). Semi-random backoff: Towards resource reservation for channel access in wireless LANs. IEEE/ACM Transactions on Networking, 21(1), 204–217.

    Article  Google Scholar 

  33. Han, K., Luo, J., Liu, Y., & Vasilakos, A. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks, a survey. IEEE Communications Magazine, 51(7), 107–113.

    Article  Google Scholar 

  34. Song, Y., et al. (2014). A biology-based algorithm to minimal exposure problem of wireless sensor networks. IEEE Transactions on Network and Service Management, 11(3), 417–430.

    Article  Google Scholar 

  35. Liu, L., et al. (2015). Physarum optimization, a biology-inspired algorithm for the steiner tree problem in networks. IEEE Transactions on Computers, 64(3), 819–832.

    MathSciNet  Google Scholar 

  36. Zhu, X., Shen, L., & Yum, T. P. (2011). Hausdorff clustering and minimum energy routing for wireless sensor networks. IEEE Transaction on Vehicular Technology, 58(2), 990–997.

    Article  Google Scholar 

  37. Uddin, M. F. (2015). Throughput analysis of a CSMA based WLAN with successive interference cancellation under Rayleigh fading and shadowing. Wireless Networks,. doi:10.1007/s11276-015-1038-5.

    Google Scholar 

  38. Uddin, M. F., Rosenberg, C., Zhuang, W., Mitran, P., & Girard, A. (2014). Joint routing and medium access control in fixed random access wireless multihop networks. IEEE/ACM Transactions on Networking, 22(1), 80–93.

    Article  Google Scholar 

  39. Sengupta, S., et al. (2012). An evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networks. IEEE Transactions on Systems, Man, and Cybernetics, Part C, 42(6), 1093–1102.

    Article  Google Scholar 

  40. Jing, Q., et al. (2014). Security of the internet of things: Perspectives and challenges. Wireless Networks, 20(8), 2481–2501.

    Article  Google Scholar 

Download references

Acknowledgments

This research was partially supported by the National Natural Science Foundation of China (NSFC) (Grant No. 41306050), the Guangdong Provincial Natural Science Foundation of China (Grant Nos. S2012010008261; 2015A030313617), and project of enhancing school with innovation of Guangdong Ocean University under Grant No. GDOU2014050228. Evaluation experts of this paper put forward the precious opinion, and his advice is very helpful to improving the quality of this paper, thank you.

Author information

Authors and Affiliations

  1. School of Information, Guangdong Ocean University, Zhanjiang, 524088, Guangdong, China

    Ji Wang, Xiaoli Ren & Guobao Xu

  2. Institute of Electronics and Information, South China University of Technology, Guangzhou, 510641, Guangdong, China

    Fang-jiong Chen & Yankun Chen

Authors
  1. Ji Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoli Ren
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fang-jiong Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yankun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Guobao Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ji Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, J., Ren, X., Chen, Fj. et al. On MAC optimization for large-scale wireless sensor network. Wireless Netw 22, 1877–1889 (2016). https://doi.org/10.1007/s11276-015-1073-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-015-1073-2

Keywords

Search

Navigation