Wireless sensor network has been used as a landslide monitoring tool for
more than one decade. The robustness of the network is important as the systems
need to survive in harsh conditions. In this paper, we consider the living time
of the sensor network under the influences of the small-scale landslide. We
investigate the performance of famous energy-efficient routing protocol PEGASIS
in both landslide case and non-landslide case. Genetic Algorithm is also
applied to enhance the effectiveness of PEGASIS. The simulation results in this
paper showed that the Genetic Algorithm helps to delay the first node death if
it is used at the beginning of data transmission while being used every round
helps to prolong last node death slightly. The impact of the Genetic Algorithm
on energy usage and route length is also examined.Under the
effect of landslide, with only 70% of energy are spent, the simulated protocols reduced around 30% equivalent route
length while managed to keep the living time up the network up to 90.76%,
comparing to cases with no landslide.
References
[1]
Othman, M.F. and Shazali, K. (2012) Wireless Sensor Network Applications: A Study in Environment Monitoring System. Procedia Engineering, 41, 1204-1210.
https://doi.org/10.1016/j.proeng.2012.07.302
[2]
Ramesh, M.V., Kumar, S. and Rangan, P.V. (2009) Wireless Sensor Network for Landslide Detection. Proceedings of the 2009 International Conference on Wireless Networks, Las Vegas, 13-16 July 2009, 89-95.
https://doi.org/10.1109/SENSORCOMM.2009.67
[3]
Rosi, A., Berti, M., Bicocchi, N., Castelli, G., Corsini, A., Mamei, M. and Zambonelli, F. (2011) Landslide Monitoring with Sensor Networks: Experiences and Lessons Learnt from a Real-World Deployment. International Journal of Sensor Networks, 10, 111-122. https://doi.org/10.1504/IJSNET.2011.042195
[4]
Sheth, A., Thekkath, C.A., Mehta, P., Tejaswi, K., Parekh, C., Singh, T.N. and Desai, U.B. (2007) Senslide: A Distributed Landslide Prediction System. ACM SIGOPS Operating Systems Review, 41, 75-87. https://doi.org/10.1145/1243418.1243428
[5]
Dixon, N., Spriggs, M.P., Meldrum, P., Ogilvy, R., Haslam, E. and Chambers, J. (2010) Development of a Low-Cost Acoustic Emission Early Warning System for Slope Instability. Proceedings of the 11th IAEG Congress, Auckland, 5-10 September 2010, 1803-1810.
[6]
Intrieri, E., Gigli, G., Mugnai, F., Fanti, R. and Casagli, N. (2012) Design and Implementation of a Landslide Early Warning System. Engineering Geology, 147-148, 124-136. https://doi.org/10.1016/j.enggeo.2012.07.017
[7]
Selvam, S., Manisha, A., Vidhya, J. and Venkatramanan, S. (2019) Fundamentals of GIS. In: GIS and Geostatistical Techniques for Groundwater Science, Chapter 1, Elsevier, Amsterdam, 3-15. https://doi.org/10.1016/B978-0-12-815413-7.00001-8
[8]
Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E. and Savage, W.Z. (2008) Guidelines for Landslide Susceptibility, Hazard and Risk Zoning for Land Use Planning. Engineering Geology, 102, 85-98.
https://doi.org/10.1016/j.enggeo.2008.03.022
[9]
Heinzelman, W.R., Chandrakasan, A. and Balakrishnan, H. (2000) Energy-Efficient Communication Protocol for Wireless Microsensor Networks. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Maui, Vol. 2, 10 p.
[10]
Lindsey, S. and Raghavendra, C.S. (2002) PEGASIS: Power-Efficient Gathering in Sensor Information Systems. Proceedings, IEEE Aerospace Conference, Big Sky, 3.
[11]
Manap, Z., Ali, B.M., Ng, C.K., Noordin, N.K. and Sali, A. (2013) A Review on Hierarchical Routing Protocols for Wireless Sensor Networks. Wireless Personal Communications, 72, 1077-1104. https://doi.org/10.1007/s11277-013-1056-5
[12]
Tejaswi, K., Mehta, P., Bansal, R., Parekh, C., Merchant, S.N. and Desai, U.B. (2006) Routing Protocols for Landslide Prediction Using Wireless Sensor Networks. 2006 Fourth International Conference on Intelligent Sensing and Information Processing, Bangalore, 43-47. https://doi.org/10.1109/ICISIP.2006.4286057
[13]
Zattas, A. (2020) PEGASIS (Power-Efficient Gathering in Sensor Information Systems).
https://www.mathworks.com/matlabcentral/fileexchange/67504-pegasis-power-efficient-gathering-in-sensor-information-systems
[14]
Gutin, G., Yeo, A. and Zverovich, A. (2002) Traveling Salesman Should Not Be Greedy: Domination Analysis of Greedy-Type Heuristics for the TSP. Discrete Applied Mathematics, 117, 81-86. https://doi.org/10.1016/S0166-218X(01)00195-0
[15]
Reeves, C. (2003) Genetic Algorithms. In: Glover, F. and Kochenberger, G.A., Eds., Handbook of Metaheuristics, International Series in Operations Research & Management Science, Vol. 57, Springer, Boston, 55-82.
https://doi.org/10.1007/0-306-48056-5_3
[16]
Somauroo, A. and Bassoo, V. (2019) Energy-Efficient Genetic Algorithm Variants of PEGASIS for 3D Wireless Sensor Networks. Applied Computing and Informatics. https://doi.org/10.1016/j.aci.2019.07.002
[17]
Petrea, D., Stefan, B., Rosca, S., Vescan, I. and Fodorean, I. (2014) The Determination of the Landslide Occurrence Probability by GIS Spatial Analysis of the Land Morphometric Characteristics (Case Study: The Transylvanian Plateau). Carpathian Journal of Earth and Environmental Sciences, 9, 91-102.
[18]
Kirk, J. (2020) Open Traveling Salesman Problem—Genetic Algorithm.
https://www.mathworks.com/matlabcentral/fileexchange/21196-open-traveling-salesman-problem-genetic-algorithm
