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Maximum lifetime routing problem in asynchronous duty-cycled wireless sensor networks

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Abstract

In this paper the problem of maximum lifetime routing is investigated in asynchronous duty-cycled wireless sensor networks. To model this problem, a new energy balance based asynchronous MAC protocol is proposed called K-Persistent FRTS–RCTS, which stands for K-Persistent flooding of RTS and random sending of CTS. In this protocol, each transmitter in order to send a data packet, first transmits at most K packets of RTS to its neighbors by flooding, but if the transmitter does not receive any CTS packets, it transmits the RTS packet directly to the sink. The CTS packet is sent to the transmitter either by one of the waking neighbors via a uniform random mechanism or by the sink node in response to the received RTS packet. It is shown that by using K-Persistent FRTS–RCTS MAC, the problem is formulated as a mixed integer nonlinear programming problem. In this problem, the optimization variables consist of the maximum number of RTS flooding requests (K) as the integer values and the flow rate of information on any route and the duty cycle of nodes both as the real values. To assess the performance of the proposed method, it is compared to the same maximum lifetime routing problem under the 1-Persistent FRTS–RCTS and the well-known X-MAC protocols. Evaluation results indicate that K-Persistent FRTS–RCTS MAC outperforms two mentioned MAC protocols in terms of both network lifetime and topology changes.

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References

  1. Daojing, H., Chun, C., Chan, S., Jiajun, B., & Vasilakos, A. V. (2012). A distributed trust evaluation model and its application scenarios for medical sensor networks. IEEE Transactions on Information Technology in Biomedicine, 16(6), 1164–1175.

    Article  Google Scholar 

  2. Xingbo, W., Minyue, F., & Huanshui, Z. (2012). Target tracking in wireless sensor networks based on the combination of KF and MLE using distance measurements. IEEE Transactions on Mobile Computing, 11(4), 567–576.

    Article  Google Scholar 

  3. Chen, M., Gonzalez, S., Vasilakos, A., Cao, H., & Leung, V. M. (2011). Body area networks: A survey. Mobile Networks and Applications, 16(2), 171–193.

    Article  Google Scholar 

  4. Zhengguo, S., Shusen, Y., Yifan, Y., Vasilakos, A., McCann, J., & Kin, L. (2013). A survey on the ietf protocol suite for the internet of things: Standards, challenges, and opportunities. IEEE Wireless Communications, 20(6), 91–98.

    Article  Google Scholar 

  5. Peng, M., Chen, H., Xiao, Y., Ozdemir, S., Vasilakos, A. V., & Wu, J. (2011). Impacts of sensor node distributions on coverage in sensor networks. Journal of Parallel and Distributed Computing, 71(12), 1578–1591.

    Article  MATH  Google Scholar 

  6. Sengupta, S., Das, S., Nasir, M., Vasilakos, A. V., & Pedrycz, W. (2012). An evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networks. IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews, 42(6), 1093–1102.

    Article  Google Scholar 

  7. Naderi, H., Kangavari, M., & Okhovvat, M. (2014). ScEP: A scalable and energy aware protocol to increase network lifetime in wireless sensor networks. Wireless Personal Communications,. doi:10.1007/s11277-014-2243-8.

    Google Scholar 

  8. Zhang, J., Liu, Y., Sun, D., & Li, B. (2014). Prolonging the lifetime of wireless sensor networks by utilizing feedback control. Wireless Networks, 20(7), 2095–2107.

    Article  Google Scholar 

  9. Kariman-Khorasani, M., Pourmina, M. A., & Salahi, A. (2015). Energy balance based lifetime maximization in wireless sensor networks employing joint routing and asynchronous duty cycle scheduling techniques. Wireless Personal Communications,. doi:10.1007/s11277-015-2439-6.

    Google Scholar 

  10. Mostafaei, H., & Shojafar, M. (2015). A new meta-heuristic algorithm for maximizing lifetime of wireless sensor networks. Wireless Personal Communications,. doi:10.1007/s11277-014-2249-2.

    MATH  Google Scholar 

  11. Boulfekhar, S., & Benmohammed, M. (2013). A novel energy efficient and lifetime maximization routing protocol in wireless sensor networks. Wireless Personal Communications, 72(2), 1333–1349.

    Article  Google Scholar 

  12. Kacimi, R., Dhaou, R., & Beylot, A.-L. (2013). Load balancing techniques for lifetime maximizing in wireless sensor networks. Ad Hoc Networks, 11(8), 2172–2186.

    Article  Google Scholar 

  13. Ok, C.-S., Lee, S., Mitra, P., & Kumara, S. (2009). Distributed energy balanced routing for wireless sensor networks. Computers and Industrial Engineering, 57(1), 125–135.

    Article  Google Scholar 

  14. Yardibi, T., & Karasan, E. (2010). A distributed activity scheduling algorithm for wireless sensor networks with partial coverage. Wireless Networks, 16(1), 213–225.

    Article  Google Scholar 

  15. Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks, 7(3), 537–568.

    Article  Google Scholar 

  16. Buettner, M., Yee, G. V., Anderson, E., & Han, R. (2006). X-MAC: A short preamble MAC protocol for duty-cycled wireless sensor networks. In Proceedings of the 4th international conference on Embedded networked sensor systems, Boulder, Colorado, USA.

  17. Yang, X., Miao, P., Gibson, J., Xie, G. G., Ding-Zhu, D., & Vasilakos, A. V. (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 

  18. Jang, B., Lim, J. B., & Sichitiu, M. L. (2013). An asynchronous scheduled MAC protocol for wireless sensor networks. Computer Networks, 57(1), 85–98.

    Article  Google Scholar 

  19. Polastre, J., Hill, J., & Culler, D. (2004). Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd international conference on Embedded networked sensor systems, Baltimore, USA (pp. 95–107).

  20. Wei, Y., 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 

  21. Kai, H., Jun, L., Yang, L., & Vasilakos, A. V. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine, 51(7), 107–113.

    Article  Google Scholar 

  22. Mo, L., Zhenjiang, L., & Vasilakos, A. V. (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 

  23. Anastasi, G., Conti, M., & Di Francesco, M. (2009). Extending the lifetime of wireless sensor networks through adaptive sleep. IEEE Transactions on Industrial Informatics, 5(3), 351–365.

    Article  Google Scholar 

  24. Yanjun, Y., Qing, C., & Vasilakos, A. V. (2013). EDAL: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for wireless sensor networks. In Proceedings of the 10th international conference on mobile ad-hoc and sensor systems (MASS) (pp. 182–190).

  25. Amgoth, T., & Jana, P. K. (2014). Energy-aware routing algorithm for wireless sensor networks. Computers & Electrical Engineering,. doi:10.1016/j.compeleceng.2014.07.010.

    Google Scholar 

  26. Yao, Y., Cao, Q., & Vasilakos, A. V. (2014). EDAL: An energy-efficient, delay-aware, and lifetime-balancing data collection protocol for heterogeneous wireless sensor networks. IEEE/ACM Transactions on Networking, PP(99), 1–1.

  27. Zeng, Y., Xiang, K., Li, D., & Vasilakos, A. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.

    Article  Google Scholar 

  28. Xiaoguang, Z., & Zheng Da, W. (2010). Energy balanced routing strategy in wireless sensor networks. In IEEE/IFIP 8th international conference on embedded and ubiquitous computing (EUC) (pp. 436–443).

  29. Chang, J.-H., & Tassiulas, L. (2004). Maximum lifetime routing in wireless sensor networks. IEEE/ACM Transactions on Networking, 12(4), 609–619.

    Article  Google Scholar 

  30. Madan, R., & Lall, S. (2006). Distributed algorithms for maximum lifetime routing in wireless sensor networks. IEEE Transactions on Wireless Communications, 5(8), 2185–2193.

    Article  Google Scholar 

  31. Park, J., & Sahni, S. (2006). An online heuristic for maximum lifetime routing in wireless sensor networks. IEEE Transactions on Computers, 55(8), 1048–1056.

    Article  Google Scholar 

  32. Paschalidis, I. C., & Wu, R. (2012). Robust maximum lifetime routing and energy allocation in wireless sensor networks. International Journal of Distributed Sensor Networks,. doi:10.1155/2012/523787.

    MATH  Google Scholar 

  33. Chilamkurti, N., Zeadally, S., Vasilakos, A., & Sharma, V. (2009). Cross-layer support for energy efficient routing in wireless sensor networks. Journal of Sensors,. doi:10.1155/2009/134165.

    Google Scholar 

  34. Hua, C., & Peter Yum, T.-S. (2008). Data aggregated maximum lifetime routing for wireless sensor networks. Ad Hoc Networks, 6(3), 380–392.

    Article  Google Scholar 

  35. Hua, C., & Yum, T.-S. P. (2008). Optimal routing and data aggregation for maximizing lifetime of wireless sensor networks. IEEE/ACM Transactions on Networking, 16(4), 892–903.

    Article  Google Scholar 

  36. Liu, X., Jun, L., & Vasilakos, A. (2011). Compressed data aggregation for energy efficient wireless sensor networks. In 8th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks (SECON) (pp. 46–54).

  37. Liu, X. Y., Zhu, Y., Kong, L., Liu, C., Gu, Y., Vasilakos, A. V., et al. (2014). CDC: Compressive data collection for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, PP(99), 1–1.

  38. Kartal Cetin, B., Prasad, N. R., & Prasad, R. (2013). Maximum lifetime routing problem in duty-cycling sensor networks. Wireless Personal Communications, 72(1), 101–119.

    Article  Google Scholar 

  39. Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.

    Article  Google Scholar 

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Correspondence to Mohsen Kariman-Khorasani.

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Kariman-Khorasani, M., Pourmina, M.A. Maximum lifetime routing problem in asynchronous duty-cycled wireless sensor networks. Wireless Netw 21, 2501–2517 (2015). https://doi.org/10.1007/s11276-015-0931-2

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