A Comparative Study of Energy Consumption Required for Localization in Wireless Sensor Networks
Localization is a key stage in building a routing matrix between nodes in wireless sensor networks. It is essential for guaranteeing the proper exchange of sensor node measurements and the conclusions made at the network level. This paper reviews various range-based localization techniques used in wireless sensor networks. It presents a mathematical model for determining sensor locations based on Received Signal Strength Indicator measurements and studies the energy consumption of the proposed localization technique. The localization technique under consideration uses Trilateration in order to find initial estimates of the coordinates of the sensor nodes. It then applies Recursive Least Square Estimation in order to refine the estimates and account for the noise accompanying the RSSI measurements. Both decentralized and centralized implementations are compared in terms of mathematical complexity, processing energy requirements, communication energy consumption, and scalability. Simulations based on the Mica2Dot platform show that besides being scalable, the decentralized localization approach becomes more energy efficient than the centralized one in terms of communication and processing power consumption as the sensors’ distribution density increases.
Copyright © 2019 Praise Worthy Prize - All rights reserved.
Bianchi, P. Ciampolini, and I. De Munari, RSSI-based indoor localization and identification for ZigBee wireless sensor networks in smart homes, IEEE Trans. Instrum. Meas., vol. 68, no. 2, pp. 566–575, Feb. 2019
El Abbassi, M., Jilbab, A., Bourouhou, A., A Robust Model of Multi-Sensor Data Fusion Applied in Wireless Sensor Networks for Fire Detection, (2016) International Review on Modelling and Simulations (IREMOS), 9 (3), pp. 173-180.
K. Darabkh, S. Ismail, M. Al-Shurman, I. Jafar, E. Alkhader, M. Al-Mistarihi, Performance evaluation of selective and adaptive heads clustering algorithms over wireless sensor networks, Journal of Network and Computer Applications, Vol. 35 (Issue 6), pp. 2068-2080, 2012.
Bani Yassein, M., Hamdan, M., Shehadeh, H., Mrayan, L., A Novel Approach for Health Monitoring System Using Wireless Sensor Network, (2017) International Journal on Communications Antenna and Propagation (IRECAP), 7 (4), pp. 271-281.
Anup Kumar Paul, and Takuro Sato, Localization in Wireless Sensor Networks: A Survey on Algorithms, Measurement Techniques, Applications and Challenges, Journal of sensor and Actuator Networks, Vol. 6 (Issue 4), 2017.
T. J. S. Chowdhury, C. Elkin, V. Devabhaktuni, D. B. Rawat, and J. Oluoch, Advances on localization techniques for wireless sensor networks: A survey, Comput. Netw., vol. 110, pp. 284–305, Dec. 2016.
Amitangshu Pal, Localization Algorithms in Wireless Sensor Networks: Current Approaches and Future Challenges, Network Protocols & Algorithms, Vol. (Issue 1), pp. 45-73, 2010.
Hadir, A., Zine-Dine, K., Bakhouya, M., El Kafi, J., Gaber, J., An Enhanced DV-Hop for Nodes Localization in Static and Mobile Wireless Sensor Networks, (2017) International Review on Computers and Software (IRECOS), 12 (3), pp. 134-144.
Tomic, S.; Beko, M.; Dinis, R., Distributed RSS-Based Localization in Wireless Sensor Networks Based on Second-Order Cone Programming, Sensors, Vol. 14, pp. 18410-18432, 2014.
Du ZhiGuo, and DaHui Hu, An improved WSN localization algorithm, 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016), Atlantis Press, 2016.
H. P. Mistry and N. H. Mistry, RSSI Based Localization Scheme in Wireless Sensor Networks: A Survey, 2015 Fifth International Conference on Advanced Computing & Communication Technologies, Haryana, 2015.
Challa, S. Leipold, F. Deshpande, S.K. Liu, M., Simultaneous localization and mapping in wireless sensor networks, Proc. of the 2005 International Conference on Intelligent Sensors, Sensor Networks and Information Processing Conference (ISSINIP 2005), 2005. pp. 81- 87, Dec. 2005.
Mohammad Al-Hattab, Maen Takruri, Hussain Attia and Huthaifa Al-Omari, Decentralized localization in wireless sensor networks, Proceedings of the 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA), Nov, 2017.
W. Wang, X. Liu, M. Li, Z. Wang and C. Wang, Optimizing Node Localization in Wireless Sensor Networks Based on Received Signal Strength Indicator, in IEEE Access, vol. 7, pp. 73880-73889, 2019.
S. Halder, A Ghosal, A survey on mobility-assisted localization techniques in wireless sensor networks, Journal of Network and Computer Applications, Volume 60, 2016, Pages 82-94.
S. Sadowski and P. Spachos, Rssi-based indoor localization with the internet of things, IEEE Access, vol. 6, pp. 30149-30161, 2018.
Zahid Farid, Rosdiadee Nordin, Mahamod Ismail, and Nor Fadzilah Abdullah, Hybrid Indoor-Based WLAN-WSN Localization Scheme for Improving Accuracy Based on Artificial Neural Network, Mobile Information Systems, vol. 2016, Article ID 6923931, 11 pages, 2016.
Goldoni, Emanuele, Luca Prando, Anna Vizziello, Pietro Savazzi, and Paolo Gamba. Experimental data set analysis of RSSI-based indoor and outdoor localization in LoRa networks, Internet Technology Letters 2, no. 1 (2019): e75.
G. Han, J. Jiang, C. Zhang, T. Q. Duong, M. Guizani and G. K. Karagiannidis, A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks, in IEEE Communications Surveys & Tutorials, Vol. 18 (Issue 3), pp. 2220-2243, 2016
F. Yaghoubi, A. A. Abbasfar and B. Maham, Energy-Efficient RSSI-Based Localization for Wireless Sensor Networks, in IEEE Communications Letters, Vol. 18 (Issue 6), pp. 973-976, 2014.
H. Khan, M. Hayat and Z. Rehman, Wireless Sensor Networks Free-Range Base Localization Schemes: A Comprehensive Survey, Proceedings of 2017 International Conference on Communication, Computing and Digital Systems (C-CODE), 2017.
Fan, H., Caffery, J.J., Jr., and Yan, C., Distributed Sensor Self-Localization, in Proceedings of IEEE MSWCAS 2005, vol. 1 , pp. 351- 354, 2005.
N. A. Azmi, S. Samsul, Y. Yamada, M. F. Mohd Yakub, M. I. Mohd Ismail and R. A. Dziyauddin, A Survey of Localization using RSSI and TDoA Techniques in Wireless Sensor Network: System Architecture, 2018 2nd International Conference on Telematics and Future Generation Networks (TAFGEN), Kuching, 2018, pp. 131-136.
Ruiz, J. C., Rosiles, J. G., Sifuentes, E., & Rivas- Perea, P., A low-complexity geometric bilateration method for localization in wireless sensor networks and its comparison with least-squares methods, Sensors, Vol 12(Issue 1), pp. 839–862, 2012.
D. Izadi, J. Abawajy, S. Ghanavati, An alternative node deployment scheme for WSNs, IEEE Sensors J., vol. 15 (Issue 2), pp. 667-675, Feb. 2015.
S. Kumar, and R. M. Hegde, A Review of Localization and Tracking Algorithms in Wireless Sensor Networks, Networking and Internet Architecture (cs.NI) 9 Jan 2017, USA.
Slavisa Tomic, Marko Beko, Rui Dinis, Paulo Montezuma, Distributed algorithm for target localization in wireless sensor networks using RSS and AoA measurements, Pervasive and Mobile Computing, Volume 37, 2017, Pages 63-77.
Z. M. Livinsa and S. Jayashri, Performance analysis of diverse environment based on RSSI localization algorithms in wsns, 2013 IEEE Conference on Information & Communication Technologies, Thuckalay, Tamil Nadu, India, pp. 572-576, 2013.
Amtel, Atmega128L processor, Rev. 2467X–AVR–06/11 datasheet, 2011.
Texas Instruments, CC1000 Single Chip Very Low Power RF Transceiver, SWRS048A datasheet, 2009.
Rappaport, Theodore S., Wireless Communications: Principles and Practice (Prentice Hall PTR), 2002.
Shnayder V, Hempstead M, Chen BR, Allen GW, Welsh M. Simulating the power consumption of large-scale sensor network applications. In Proceedings of the 2nd international conference on Embedded networked sensor systems pp. 188-200, Nov 2004.
Williams, Virginia Vassilevska. Multiplying matrices faster than Coppersmith-Winograd, Proceedings of the Annual ACM Symposium on Theory of Computing, May 2012.
Richard P. Brent, Multiple-precision zero-finding methods and the complexity of elementary function evaluation, in: Analytic Computational Complexity (J. F. Traub, ed.), (Academic Press, 1975, 151–176).
Jonathan M. Borwein & Peter B. Borwein, Pi and the AGM: A Study in Analytic Number Theory and Computational Complexity, (Wiley Interscience, 1987).
Farebrother, R.W. (1988), Linear Least Squares Computations, STATISTICS: Textbooks and Monographs (CRC Press, 1988).
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2021 Praise Worthy Prize