Abstract
Node flip ambiguity is a key problem that needs to be addressed for range-based node localization in wireless sensor networks. In this paper we have implemented robustness analysis for node multilateration localization in wireless sensor networks. A robustness criterion, called orthogonal projection algorithm (OPA), to detect flip ambiguity for range-based nodes multilateration localization method is proposed. The basic idea of OPA comes from the orthogonal projection principle, and it has the low computational complexity. On the basis of OPA, we further derive an expression to quantify the probability of flip ambiguity occurrences. Theoretical analysis and numerical simulation results demonstrate that OPA has good detection results and the low computational complexity, the expression for calculating probability of flip ambiguity occurrences is feasible.
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Li, J. L., & AlRegib, G. (2009). Distributed estimation in energy-constrained wireless sensor networks. IEEE Transactions on Signal Processing, 9(6), 897–910.
Vasilakos, A. V. (2008). Special issue: Ambient intelligence. Information Sciences, 178(3), 585–587.
Sheng, Z. G., Yang, S. S., Yu, Y. F., Vasilakos, A. V., McCann, J. A., & Leung, K. K. (2013). A survey on the IETF protocol suite for the internet of things: standards, challenges, and opportunities. IEEE Wireless Communications, 20(6), 91–98.
Zhou, Y. Z., Zhang, Y. X., Liu, H., Xiong, N. X., & Vasilakos, A. V. (2014). A bare-metal and asymmetric partitioning approach to client virtualization. IEEE Transactions on Services Computing, 7(1), 40–53.
Bartolini, N., Bongiovanni, G., La Porta, T. F., & Silvestri, S. (2014). On the vulnerabilities of the virtual force approach to mobile sensor deployment. IEEE Transactions on Mobile Computing, 63(5), 307–320.
Zeng, Y. Y., Li, D. S., & Vasilakos, A. V. (2013). Real-time data report and task execution in wireless sensor and actuator networks using self-aware mobile actuators. Computer Communications, 36(9), 988–997.
Wei, G. Y., Ling, Y., Guo, B. F., Xiao, B., & Vasilakos, A. V. (2011). Prediction-based data aggregation in wireless sensor networks: Combining grey model and Kalman filter. Computer Communications, 34(6), 793–802.
Yao, Y.J., Cao, Q., & 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 IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS’13).
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, 42(6), 1093–1102.
Nasser, N., Karim, L., & Taleb, T. (2013). Dynamic multilevel priority packet scheduling scheme for wireless sensor network. IEEE Transactions on Wireless Communications, 12(4), 1448–1459.
Yao, Y. J., 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. doi:10.1109/TNET.2014.2306592.
Liu, X.Y., Zhu, Y.M., Kong, L.H., Liu, C., Gu, Y., Vasilakos, A.V., & Wu, M.Y. CDC: compressive data collection for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems. doi:10.1109/TPDS.2014.2345257.
Yildirim, K. S., & Kantarci, A. (2013). Time synchronization based on slow-flooding in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 25(1), 244–253.
Lamonaca, F., Gasparri, A., Garone, E., & Grimaldi, D. (2014). Cock synchronization in wireless sensor network with selective convergence rate for event driven measurement applications. IEEE Transactions on Instrumentation and Measurement, 63(9), 2279–2287.
Li, M., Li, Z. J., & 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.
Cheng, H. J., Xiong, N. X., Vasilakos, A. V., Tianruo, Y. L., Chen, G. L., & Zhuang, X. F. (2012). Nodes organization for channel assignment with topology preservation in multi-radio wireless mesh networks. Ad Hoc Networks, 10(5), 760–773.
Roy, S., Conti, M., Setia, S., & Jajodia, S. (2014). Secure data aggregation in wireless sensor networks: Filtering out the attacker’s impact. IEEE Transactions on Information Forensics and Security, 9(4), 681–694.
Han, K., Luo, J., Liu, Y., & Vasilakos, A. V. (2013). Algorithm design for data communications in duty-cycled wireless sensor networks: A survey. IEEE Communications Magazine, 51(7), 107–113.
Chai, Y.Z., & Dong, E.Q. (2011). A three-dimensional localization algorithm for wireless sensor networks based on the BFGS optimization. In Proceedings of the 11th European Wireless Conference (EW’11).
Gribben, J., & Boukerche, A. (2014). Location error estimation in wireless ad hoc networks. Ad Hoc Networks, 13, 504–515.
Tan, G., Jiang, H. B., Zhang, S. K., Yin, Z. M., & Kermarrec, A. M. (2013). Connectivity-based and anchor-free localization in large-scale 2D/3D sensor networks. ACM Transactions on Sensor Networks. doi:10.1145/2529976.
Chai, Y.Z., Dong, E.Q., & Liu, X.J. (2011). A novel three-dimensional localization algorithm for Wireless Sensor Networks based on Particle Swarm Optimization. In Proceedings of the 18th International Conference on Telecommunications (ICT’11).
Shi, Q.J., He, C., Chen, H.Y., & Jiang, L.G. (2010). Distributed wireless sensor network localization via sequential greedy optimization algorithm. IEEE Transactions on Signal Processing, 5896), 3328–3340.
Aspnes, J., Eren, T., Goldenberg, D. K., Morse, A. S., Whiteley, W., Yang, Y. R., et al. (2006). A theory of network localization. IEEE Transactions on Mobile Computing, 5(12), 1663–1678.
Connelly, R. (2005). Generic global rigidity. Discrete and Computational Geometry, 33(4), 549–563.
Kannan, A. A., Fidan, B., & Mao, G. Q. (2011). Use of flip ambiguity probabilities in robust sensor network localization. Wireless Networks, 17(5), 1157–1171.
Moore, D., Leonard, J., Rus, D., & Teller, S. (2004). Robust distributed network localization with noisy range measurements. In Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems (SenSys’04).
Sittile, F. & Spirito, M. (2008). Robust localization for wireless sensor networks. In Proceedings of the 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON’08).
Kannan, A. A., Fidan, B., Mao, G. Q., & Anderson, B. D. O. (2007). Analysis of flip ambiguities in distributed network localization. In Proceedings of Information, Decision and Control (IDC’07).
Kannan, A. A., Fidan, B., & Mao, G. Q. (2010). Analysis of flip ambiguities for robust sensor network localization. IEEE Transactions on Vehicular Technology, 59(4), 2057–2070.
Chen, D.S., Li, X.Y., Xiao, W., & Wang, T. M. (2011). An improved quadrilateral localization algorithm for wireless sensor networks. In Proceedings of IEEE/ICME International Conference on Complex Medical Engineering (CME’11).
Wang, X. P., Yang, Z., Luo, J., & Shen, C. X. (2011). Beyond rigidity: Obtain localizability with noisy ranging measurement. International Journal of Ad Hoc and Ubiquitous Computing, 8(1), 114–124.
Poggi, C. & Mazzini, G. (2003). Collinearity for sensor network localization. In Proceedings of the 58th IEEE Vehicular Technology Conference (VTC’03).
Houle, M. E., & Toussaint, G. T. (1988). Computing the width of a set. IEEE Transactions on Pattern Analysis and Machine Intelligence, 10(5), 761–765.
Rahman, M., & Kleeman, L. (2009). Paired measurement localization: Arobust approach for wireless localization. IEEE Transactions on Mobile Computing, 8(8), 1087–1102.
Severi, S., Abreu, G., Destino, G. & Dardari, D. (2009). Understanding and solving flip-ambiguity in network localization via semidefinite programming. In Proceedings of Global Telecommunications Conference (GLOBECOM’09).
Wang, X. P., Liu, Y. H., Yang, Z., Lu, K., & Luo, J. (2013). OFA: An optimistic approach to conquer flip ambiguity in network localization. Computer Networks, 57(6), 1529–1544.
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This work was supported in part by the National Natural Science Foundation of China under Grant 81371635, Research Fund for the Doctoral Program of Higher Education of China under Grant 20120131110062, Science and Technology Development Projects of Shandong province under Grant 2013GGX10104.
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Liu, W., Dong, E. & Song, Y. Robustness analysis for node multilateration localization in wireless sensor networks. Wireless Netw 21, 1473–1483 (2015). https://doi.org/10.1007/s11276-014-0865-0
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DOI: https://doi.org/10.1007/s11276-014-0865-0