Sensor Activity Scheduling Protocol for Lifetime prolongation in Wireless Sensor Networks
https://doi.org/10.24017/science.2017.3.12
Abstract views: 1057 / PDF downloads: 887Abstract
In Wireless Sensor Network (WSN), the dense sensor nodes deployment in the sensing field can be exploited in conserving the energy of the whole network, where the data of these nodes can be highly correlated. Therefore, it is necessary to turn off the unnecessary nodes that sense similar sensor readings so as to reduce the redundant sensed readings and decrease the communication overhead thus extend the WSN lifetime. This article suggests a Sensor Activity Scheduling (SAS) protocol for lifetime improvement of WSNs. SAS works in a periodic way. It exploits the spatial correlation among sensed sensor data in order to produce the best sensor activities schedule in WSNs. SAS composed of three phases: data collection, decision-based optimization, and sensing. SAS measures the similarity degree among the sensed data that collected in the first phase. It makes a decision of which sensors stay active during the sensing phase in each period and put the other nodes into low power sleep whilst keeping a good accuracy level to the received data at the sink to conserve the power and enhance the lifetime of the WSN. Several experiments based on real sensed data and by using OMNeT++ simulator demonstrate that SAS can save energy and extend the WSN lifetime efficiently compared with the other methods.
Keywords:
WSNs, scheduling, optimization, energy saving, Metaheuristic, spatial correlation.
References
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https://doi.org/10.25212/lfu.qzj.2.2.22
https://doi.org/10.1109/PIMRC.2015.7343631
[2] D. D. Koo, J. J. Lee, A. Sebastiani, J. Kim, "An Internet-of-Things (IoT) system development and implementation for bathroom safety enhancement," Procedia Engineering 145 (2016): 396-403, 2016.
https://doi.org/10.1016/j.proeng.2016.04.004
[3] T. Bhuvaneswari, J. Hossen, C. Venkataseshiah, L.W. Xiong, "Wireless Sensor Network (WSN) based smart and safe home," Journal of Engineering and Applied Science, 12(1), pp. 127- 132, 2017.
[4] K. Vairamani, N. Mathivanan, K. A. Venkatesh, U. D. Kumar, "Environmental parameter monitoring using wireless sensor network," Instruments and Experimental Techniques, 56 (4), 468-471, 2013.
https://doi.org/10.1134/S0020441213040118
[5] K. B. Surekha, V. Raghunandan, K. G. Mohan, "Efficient Sleep Scheduling Strategy to enhance the Network Lifetime of WSN," International Journal of Engineering Research, 4 (4), pp. 323- 326, 2015.
[6] M. Wu, L. Tan, N. Xiong, "A structure fidelity approach for big data collection in wireless sensor networks," Sensors, 15(1), pp. 248-273, 2014.
https://doi.org/10.3390/s150100248
[7] H. Cheng, Z. Su, D. Zhang, J. Lloret, Z. Yu, "Energy-efficient node selection algorithms with correlation optimization in wireless sensor networks," International Journal of Distributed Sensor Networks, 10 (3), pp. 576573., 2014.
https://doi.org/10.1155/2014/576573
[8] L. I. Khudonogova, S. V. Muravyov, "Energyaccuracy aware active node selection in wireless sensor networks," In 2016 International Siberian Conference on Control and Communications (SIBCON), pp. 1-5, 2016.
https://doi.org/10.1109/SIBCON.2016.7491835
[9] J. Zhang, H. Yan, B. Wang, J. Wang, X. Fu, "Selfadaptive sleep scheduling for wireless sensor networks," International Journal of Wireless and Mobile Computing, 8 (4), pp. 346-352., 2015.
https://doi.org/10.1504/IJWMC.2015.070939
[10] E. Karasabun, I. Korpeoglu, C. Aykanat, "Active node determination for correlated data gathering in wireless sensor networks," Computer Networks, 57 (5), pp. 1124-1138., 2013.
https://doi.org/10.1016/j.comnet.2012.11.018
[11] B. Shi, W. Wei, Y. Wang, W. Shu, "A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks," Sensors, 16 (10), pp. 1702., 2016.
https://doi.org/10.3390/s16101702
[12] P. Bodik, W. Hong, C. Guestrin, S. Madden, M. Paskin, R. Thibaux, "Intel Lab Data", [Online]. Available: http://db.csail.mit.edu/labdata/labdata.html, 2004.
[13] A. Varga, "Omnet++ discrete event simulation system," [Online]. Available: http://www.omnetpp.org, 2003.
[14] X. Xu, Y. H. Hu, W. Liu, J. Bi, "Data-coverage sleep scheduling in wireless sensor networks," In Seventh International Conference on Grid and Cooperative Computing, GCC'08., pp. 342-348, 2008.
https://doi.org/10.1109/GCC.2008.9
[15] W. B. Heinzelman, A. P. Chandrakasan, H. Balakrishnan, "An application-specific protocol architecture for wireless microsensor networks," IEEE Transactions on wireless communications, 1 (4), pp. 660-670, 2002.
https://doi.org/10.1109/TWC.2002.804190
[16] F. Pedraza, A. L. Medaglia, A. Garcia, "Efficient coverage algorithms for wireless sensor networks," In 2006 IEEE Systems and Information Engineering Design Symposium, pp. 78-83, 2006.
https://doi.org/10.1109/SIEDS.2006.278717
[17] S. Dhimal, K. Sharma, "Energy conservation in wireless sensor networks by exploiting inter-node data similarity metrics," International Journal of Energy, Information and Communications, 6 (2), pp. 23-32., 2015.
https://doi.org/10.14257/ijeic.2015.6.2.03
[18] D. Arivudainambi, S. Balaji, "Improved memetic algorithm for energy efficient sensor scheduling with adjustable sensing range," Wireless Personal Communications, pp. 1-22, 2016.
https://doi.org/10.1007/s11277-016-3883-7
[19] H. M. Harb, "Energy efficient data handling and coverage for wireless sensor networks," PhD diss.,Université de Franche-Comté, 2016.
[20] T. Yu, A. M. Akhtar, A. Shami, X. Wang, "Energyefficient scheduling mechanism for indoor wireless sensor networks," In 2015 IEEE Vehicular Technology Conference (VTC Spring), pp. 1-6., 2015.
https://doi.org/10.1109/VTCSpring.2015.7145818
[21] J. C. Lim, C. Bleakley, "Adaptive WSN scheduling for lifetime extension in environmental monitoring applications," International Journal of Distributed Sensor Networks, 8 (1), pp. 286-981, 2011.
https://doi.org/10.1155/2012/286981
[22] A. K. Idrees, K. Deschinkel, M. Salomon, R. Couturier, "Coverage and lifetime optimization in heterogeneous energy wireless sensor networks," ICN 2014, pp. 60, 2014.
[23] A. K. Idrees, K. Deschinkel, M. Salomon, R. Couturier, "Distributed lifetime coverage optimization protocol in wireless sensor networks," The Journal of Supercomputing, 71 (12), pp. 4578-4593, 2015.
https://doi.org/10.1007/s11227-015-1558-x
[24] A. K. Idrees, K. Deschinkel, M. Salomon, R. Couturier, "Perimeter-based coverage optimization to improve lifetime in wireless sensor networks," Engineering Optimization, 48 (11), pp.1951-1972, 2016.
https://doi.org/10.1080/0305215X.2016.1145015
[25] A. K. M. Al-Qurabat, A. K. Idrees, "Adaptive Data Collection protocol for Extending Lifetime of Periodic Sensor Networks," Qalaai Zanist Scientific Journal, 2 (2), pp. 83 - 92, 2017.
https://doi.org/10.25212/lfu.qzj.2.2.11
[26] A. K. M. Al-Qurabat, A. K. Idrees, "Distributed Data Aggregation protocol for improving lifetime of Wireless Sensor Networks," Qalaai Zanist Scientific Journal, 2 (2), pp. 204 - 215, 2017.
https://doi.org/10.25212/lfu.qzj.2.2.22
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How to Cite
[1]
W. Hussein and A. K. Idrees, “Sensor Activity Scheduling Protocol for Lifetime prolongation in Wireless Sensor Networks”, KJAR, vol. 2, no. 3, pp. 7–13, Sep. 2017, doi: 10.24017/science.2017.3.12.
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Published
04-09-2017
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Pure and Applied Science
