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A Survey on Efficient Power Consumption in Adaptive Wireless Sensor Networks

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Abstract

The paper aims to give an extensive overview of the energy constraints in Wireless Sensor Networks and the power management strategies used in the literature as power efficiency is considered as the most challenging issue in WSNs. The paper opted for an investigative study of the adaptive systems that represent efficient solutions to deal with environmental and context changes in wireless sensor Networks. It provides thorough insights about how change has brought about the use of adaptive systems in WSNs. It proposes a new adaptation technique inspired from combining adaptation in different layers and can be more efficient and performing. This paper fulfills an identified need to study reconfigurable systems to achieve power efficiency, as a sensor node is power constrained.

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References

  1. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.

    Article  Google Scholar 

  2. Sudevalayam, S., & Kulkarni, P. (2011). Energy harvesting sensor nodes: Survey and implications. Communications Surveys & Tutorials, IEEE, 13(3), 443–461.

    Article  Google Scholar 

  3. He, T., Krishnamurthy, S., Stankovic, J. A., Abdelzaher, T., Luo, L., Stoleru, R., Yan, T., Gu, L., Hui, J., & Krogh, B. (2004). Energy-efficient surveillance system using wireless sensor networks. In Proceedings of the 2nd international conference on mobile systems, applications, and services (pp. 270–283). ACM.

  4. Jelicic, V., Magno, M., Brunelli, D., Bilas, V., & Benini, L. (2012). Analytic comparison of wake-up receivers for WSNs and benefits over the wake-on radio scheme. In Proceedings of the 7th ACM workshop on performance monitoring and measurement of heterogeneous wireless and wired networks (pp. 99–106). ACM.

  5. Aoudia, F. A., Magno, M., Gautier, M., Berder, O., & Benini, L. (2016). Wake-up receivers for energy efficient and low latency communication. In 2016 15th ACM/IEEE international conference on information processing in sensor networks (IPSN) (pp. 1–2). IEEE.

  6. Kompis, C., & Sureka, P. (2010). Power management technologies to enable remote and wireless sensing. ESP KTN, Teddington, UK, Tech. Rep.

  7. Lombardo, M., Camarero, J., Valverde, J., Portilla, J., de la Torre, E., & Riesgo, T. (2012). Power management techniques in an FPGA-based WSN node for high performance applications. In 2012 7th International workshop on reconfigurable communication-centric systems-on-chip (ReCoSoC) (pp. 1–8). IEEE.

  8. Tang, W., Ma, X., Huang, J., & Wei, J. (2015). Toward improved RPL: A congestion avoidance multipath routing protocol with time factor for wireless sensor networks. Journal of Sensors, 2016. https://doi.org/10.1155/2016/8128651.

    Google Scholar 

  9. Taneja, H., & Bhalla, P. (2013). An improved version of leach: Three levels hierarchical clustering leach protocol (TLHCLP) for homogeneous WSN. International Journal of Advanced Research in Computer and Communication Engineering, 2(9), 3610–3615.

    Google Scholar 

  10. Othman, S. B., Bahattab, A. A., Trad, A., & Youssef, H. (2015). Confidentiality and integrity for data aggregation in WSN using homomorphic encryption. Wireless Personal Communications, 80(2), 867–889.

    Article  Google Scholar 

  11. Cheng, B. H., Giese, H., Inverardi, P., Magee, J., de Lemos, R., Andersson, J., Becker, B., Bencomo, N., Brun, Y., Cukic, B., & Di Marzo Serugendo, G. (2008). 08031—Software engineering for self-adaptive systems: A research road map. In Dagstuhl seminar proceedings. Schloss Dagstuhl-Leibniz-Zentrum für Informatik.

  12. Abbes, F., Amor, N. B., & Frikha, T. (2012). Design of an adaptive 3D graphics embedded system. In Embedded and multimedia computing technology and service (pp. 39–54). Netherlands: Springer.

  13. Loukil, K., Amor, N. B., Abid, M., & Diguet, J. P. (2013). Self-adaptive on-chip system based on cross-layer adaptation approach. International Journal of Reconfigurable Computing, 2013, 6.

    Article  Google Scholar 

  14. Potdar, V., Sharif, A.,& Chang, E. (2009). Wireless sensor networks: A survey. In International conference on advanced information networking and applications workshops, 2009, WAINA’09 (pp. 636–641). IEEE.

  15. Hammel, T., & Rich, M. (2007). A higher capability sensor node platform suitable for demanding applications. In Proceedings of the 6th international conference on Information processing in sensor networks (pp. 138–147). ACM.

  16. Hsu, S. J., Wu, H. H., Chen, S. W., Liu, T. C., Huang, W. T., Chang, Y. J., Chen, C. H., & Chen, Y. Y. (2008). Development of telemedicine and telecare over wireless sensor network. In International conference on multimedia and ubiquitous engineering, 2008. MUE 2008 (pp. 597–604). IEEE.

  17. Valverde, J., Otero, A., Lopez, M., Portilla, J., De La Torre, E., & Riesgo, T. (2012). Using SRAM based FPGAs for power-aware high performance wireless sensor networks. Sensors, 12(3), 2667–2692.

    Article  Google Scholar 

  18. Portilla, J., De Castro, A., De La Torre, E., & Riesgo, T. (2006). A modular architecture for nodes in wireless sensor networks. Journal of UCS, 12(3), 328–339.

    Google Scholar 

  19. Peter, S., Stecklina, O., Portilla, J., De la Torre, E., Langendoerfer, P., & Riesgo, T. (2009). Reconfiguring crypto hardware accelerators on wireless sensor nodes. In 6th Annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks workshops, 2009. SECON Workshops’ 09 (pp. 1–3). IEEE.

  20. Liu, F., Jia, Z., & Li, Y. (2012). A novel partial dynamic reconfiguration image sensor node for wireless multimedia sensor networks. In 2012 IEEE 14th International conference on high performance computing and communication & 2012 IEEE 9th international conference on embedded software and systems (HPCC-ICESS) (pp. 1368–1374). IEEE.

  21. Kwok, T. T. O., & Kwok, Y. K. (2006). Computation and energy efficient image processing in wireless sensor networks based on reconfigurable computing. In 2006 International conference on parallel processing workshops, 2006. ICPP 2006 workshops (pp. 8). IEEE.

  22. Sun, Y., Li, L., & Luo, H. (2011). Design of FPGA-based multimedia node for WSN. In 2011 7th international conference on wireless communications, networking and mobile computing (WiCOM) (pp. 1–5). IEEE.

  23. Berder, O., & Sentieys, O. (2010). Powwow: Power optimized hardware/software framework for wireless motes. In 2010 23rd International conference on architecture of computing systems (ARCS) (pp. 1–5). VDE.

  24. Krasteva, Y., Portilla, J., de la Torre, E., & Riesgo, T. (2011). Embedded runtime reconfigurable nodes for wireless sensor networks applications. Sensors Journal IEEE, 11(9), 800–1810.

    Article  Google Scholar 

  25. Tanaka, S., Fujita, N., Yanagisawa, Y., Terada, T., & Tsukamoto, M. (2008). Reconfigurable hardware architecture for saving power consumption on a sensor node. In 2008 International conference on intelligent sensors, sensor networks and information processing, 2008. ISSNIP (pp. 405–410). IEEE.

  26. Ang, L. M., Seng, K. P., Chew, L. W., Yeong, L. S., & Chia, W. C. (2013). Wireless multimedia sensor networks on reconfigurable hardware. Berlin: Springer.

    Book  Google Scholar 

  27. Feng, J., Lian, B., & Zhao, H. (2014). Smart power management and delay reduction for target tracking in wireless sensor networks. Journal of Electrical and Computer Engineering, 2014. https://doi.org/10.1155/2014/641720.

    Google Scholar 

  28. Watkins, A., Mudhireddy, V. N., Wang, H., & Tragoudas, S. (2014). Adaptive compressive sensing for low power wireless sensors. In Proceedings of the 24th edition of the great lakes symposium on VLSI (pp. 99–104). ACM.

  29. Aziz, S. M., & Pham, D. M. (2013). Energy efficient image transmission in wireless multimedia sensor networks. Communications Letters, IEEE, 17(6), 1084–1087.

    Article  Google Scholar 

  30. Chandra, R., Mahajan, R., Moscibroda, T., Bahl, P., & Raghavendra, R. (2014). Adapting channel width for improving the performance of wireless networks. U.S. Patent 8,699,424.

  31. De La Piedra, A., Braeken, A., & Touhafi, A. (2013). A performance comparison study of ECC and AES in commercial and research sensor nodes. In EUROCON, 2013 IEEE (pp. 347–354). IEEE.

  32. Wu, F., Wei, Z., Wu, C., Chen, G., & Sheng, B. (2015). Incentive-compatible adaptive-width channel allocation for non-cooperative wireless networks. International Journal of Sensor Networks, 18(3–4), 227–237.

    Article  Google Scholar 

  33. Hussain, S. A., Razzak, M. I., Minhas, A. A., Sher, M., & Tahir, G. R. (2009). Energy efficient image compression in wireless sensor networks. International Journal of Recent Trends in Engineering (IJRTE), 1, 2.

    Google Scholar 

  34. Ben Saïd, M., Ben Amor, N., Abid, M., Ben Taher, F., & Diguet, J. P. (2011). A bi-constraints adaptation technique for embedded multimedia systems. In 2011 International conference on multimedia computing and systems (ICMCS) (pp. 1–6). IEEE.

  35. Mplemenos, G. G., Papadopoulos, K., & Papaefstathiou, I. (2010). Using reconfigurable hardware devices in WSNs for reducing the energy consumption of routing and security tasks. In 2010 IEEE global telecommunications conference (GLOBECOM 2010) (pp. 1–5). IEEE.

  36. Gamez, N., Romero, D., Fuentes, L., Rouvoy, R., & Duchien, L. (2012). Constraint-based self-adaptation of wireless sensor networks. In Proceedings of the 2nd international workshop on adaptive services for the future internet and 6th international workshop on web APIs and service mashups (pp. 20–27). ACM.

  37. Mathew, M., & Weng, N. (2014). Quality of information and energy efficiency optimization for sensor networks via adaptive sensing and transmitting. Sensors Journal, IEEE, 14(2), 341–348.

    Article  Google Scholar 

  38. Atitallah, N., Hakim, H., Loukil, K., Obeid, A. M., & Abid, M. (2016). Energy efficient adaptive transmission strategy using cooperative diversity for wireless sensor networks. In 2016 IEEE 27th annual international symposium on personal, indoor, and mobile radio communications (PIMRC) (pp. 1–6). IEEE.

  39. Raghunathan, V., Schurgers, C., Park, S., & Srivastava, M. B. (2002). Energy-aware wireless microsensor networks. Signal Processing Magazine, IEEE, 19(2), 40–50.

    Article  Google Scholar 

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Acknowledgements

This work is supported in part by the National Electronics, Communications and Photonics Research Center of King Abdulaziz City for Science and Technology (KACST).

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Authors and Affiliations

  1. National Center for MEMS Technology, King Abdulaziz City for Science and Technology (KACST), Riyadh, 11442, Saudi Arabia

    Abdulfattah Mohammad Obeid & Mohammad Bensalah

  2. CES Laboratory, National Engineering School of Sfax, University of Sfax, P.O Box 1173, 3038, Sfax, Tunisia

    Nesrine Atitallah, Kais Loukil & Mohamed Abid

  3. Digital Research Center of Sfax, B.P. 275, Sakiet Ezzit, 3021, Sfax, Tunisia

    Nesrine Atitallah, Kais Loukil & Mohamed Abid

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  1. Abdulfattah Mohammad Obeid
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  2. Nesrine Atitallah
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  3. Kais Loukil
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  4. Mohamed Abid
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  5. Mohammad Bensalah
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Correspondence to Nesrine Atitallah.

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Obeid, A.M., Atitallah, N., Loukil, K. et al. A Survey on Efficient Power Consumption in Adaptive Wireless Sensor Networks. Wireless Pers Commun 101, 101–117 (2018). https://doi.org/10.1007/s11277-018-5678-5

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