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Erschienen in: Wireless Networks 5/2019

26.04.2019

A comparative investigation of deterministic and metaheuristic algorithms for node localization in wireless sensor networks

verfasst von: Vaishali R. Kulkarni, Veena Desai, Raghavendra V. Kulkarni

Erschienen in: Wireless Networks | Ausgabe 5/2019

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Abstract

Location-based services in wireless sensor networks demand precise information of locations of sensor nodes. Range-based localization, a problem formulated as a two-dimensional optimization problem, has been addressed in this paper as a multistage exercise using bio-inspired metaheuristics. A modified version of the shuffled frog leaping algorithm (MSFLA) has been developed for accurate sensor localization. The results of MSFLA have been compared with those of geometric trilateration, artificial bee colony and particle swarm optimization algorithms. Dependance of localization accuracies achieved by these algorithms on the environmental noise has been investigated. Simulation results show that MSFLA delivers the estimates of the locations over 30% more accurately than the geometric trilateration method does in noisy environments. However, they involve higher computational expenses. The MSFLA delivers the most accurate localization results; but, it requires the longest computational time.

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Literatur
1.
Zurück zum Zitat Alrajeh, N. A., Bashir, M., & Shams, B. (2013). Localization techniques in wireless sensor networks. International Journal of Distributed Sensor Networks, 9(6), 304628.CrossRef Alrajeh, N. A., Bashir, M., & Shams, B. (2013). Localization techniques in wireless sensor networks. International Journal of Distributed Sensor Networks, 9(6), 304628.CrossRef
2.
Zurück zum Zitat 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.CrossRef 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.CrossRef
3.
Zurück zum Zitat Aydin, D. (2015). Composite artificial bee colony algorithms: From component-based analysis to high-performing algorithms. Applied Soft Computing, 32(C), 266–285.CrossRef Aydin, D. (2015). Composite artificial bee colony algorithms: From component-based analysis to high-performing algorithms. Applied Soft Computing, 32(C), 266–285.CrossRef
4.
Zurück zum Zitat Bahl, P., & Padmanabhan, V. N. (2000). RADAR: An in-building RF-based user location and tracking system. In Proceedings of the 19th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM) (pp. 775–784). Bahl, P., & Padmanabhan, V. N. (2000). RADAR: An in-building RF-based user location and tracking system. In Proceedings of the 19th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM) (pp. 775–784).
5.
Zurück zum Zitat Bansal, J. C., Sharma, H., & Jadon, S. S. (2013). Artificial bee colony algorithm: A survey. International Journal of Advanced Intelligence Paradigms, 5, 123–159.CrossRef Bansal, J. C., Sharma, H., & Jadon, S. S. (2013). Artificial bee colony algorithm: A survey. International Journal of Advanced Intelligence Paradigms, 5, 123–159.CrossRef
6.
Zurück zum Zitat Barati, M., & Farsangi, M. M. (2014). Solving unit commitment problem by a binary shuffled frog leaping algorithm. IET Generation, Transmission Distribution, 8(6), 1050–1060.CrossRef Barati, M., & Farsangi, M. M. (2014). Solving unit commitment problem by a binary shuffled frog leaping algorithm. IET Generation, Transmission Distribution, 8(6), 1050–1060.CrossRef
7.
Zurück zum Zitat Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: From natural to artificial systems. New York, NY: Oxford University Press Inc.MATH Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999). Swarm intelligence: From natural to artificial systems. New York, NY: Oxford University Press Inc.MATH
8.
Zurück zum Zitat Boukerche, A., Oliveira, H. A. B. F., Nakamura, E. F., & Loureiro, A. A. F. (2007). Localization systems for wireless sensor networks. IEEE Wireless Communications, 14(6), 6–12.CrossRef Boukerche, A., Oliveira, H. A. B. F., Nakamura, E. F., & Loureiro, A. A. F. (2007). Localization systems for wireless sensor networks. IEEE Wireless Communications, 14(6), 6–12.CrossRef
9.
Zurück zum Zitat Bulusu, N., Heidemann, J., & Estrin, D. (2000). GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications, 7(5), 28–34.CrossRef Bulusu, N., Heidemann, J., & Estrin, D. (2000). GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications, 7(5), 28–34.CrossRef
10.
Zurück zum Zitat Cao, J. (2015). A localization algorithm based on particle swarm optimization and quasi-Newton algorithm for wireless sensor networks. Journal of Communication and Computers, 10(2), 85–90. Cao, J. (2015). A localization algorithm based on particle swarm optimization and quasi-Newton algorithm for wireless sensor networks. Journal of Communication and Computers, 10(2), 85–90.
11.
Zurück zum Zitat Doherty, L., Pister, K., & El Ghaoui, L. (2001). Convex position estimation in wireless sensor networks. In Proceedings of the 20th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM) (Vol. 3, pp. 1655–1663). Doherty, L., Pister, K., & El Ghaoui, L. (2001). Convex position estimation in wireless sensor networks. In Proceedings of the 20th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM) (Vol. 3, pp. 1655–1663).
12.
Zurück zum Zitat Eusuff, M., Lansey, K., & Pasha, F. (2006). Shuffled frog-leaping algorithm: A memetic meta-heuristic for discrete optimization. Engineering Optimization, 38, 129–154.MathSciNetCrossRef Eusuff, M., Lansey, K., & Pasha, F. (2006). Shuffled frog-leaping algorithm: A memetic meta-heuristic for discrete optimization. Engineering Optimization, 38, 129–154.MathSciNetCrossRef
13.
Zurück zum Zitat Feng, C., & Zhang, L. H. (2012). A modified shuffled frog leaping algorithm for solving nodes position in wireless sensor network. Proceedings of the International Conference on Machine Learning and Cybernetics, 2, 555–559. Feng, C., & Zhang, L. H. (2012). A modified shuffled frog leaping algorithm for solving nodes position in wireless sensor network. Proceedings of the International Conference on Machine Learning and Cybernetics, 2, 555–559.
14.
Zurück zum Zitat He, K., Jia, M., & Xu, Q. (2016). Optimal sensor deployment for manufacturing process monitoring based on quantitative cause-effect graph. IEEE Transactions on Automation Science and Engineering, 13(2), 963–975.CrossRef He, K., Jia, M., & Xu, Q. (2016). Optimal sensor deployment for manufacturing process monitoring based on quantitative cause-effect graph. IEEE Transactions on Automation Science and Engineering, 13(2), 963–975.CrossRef
15.
Zurück zum Zitat Hightower, J., & Borriello, G. (2001). Location systems for ubiquitous computing. Computer, 34(8), 57–66.CrossRef Hightower, J., & Borriello, G. (2001). Location systems for ubiquitous computing. Computer, 34(8), 57–66.CrossRef
16.
Zurück zum Zitat Hsieh, T. J., Hsiao, H. F., & Yeh, W. C. (2011). Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm. Appllied Soft Computing, 11(2), 2510–2525.CrossRef Hsieh, T. J., Hsiao, H. F., & Yeh, W. C. (2011). Forecasting stock markets using wavelet transforms and recurrent neural networks: An integrated system based on artificial bee colony algorithm. Appllied Soft Computing, 11(2), 2510–2525.CrossRef
17.
Zurück zum Zitat Kar, A. K. (2016). Bio inspired computing—A review of algorithms and scope of applications. Expert Systems with Applications, 59, 20–32.CrossRef Kar, A. K. (2016). Bio inspired computing—A review of algorithms and scope of applications. Expert Systems with Applications, 59, 20–32.CrossRef
18.
Zurück zum Zitat Karaboga, D., & Basturk, B. (2007). A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm. Journal of Global Optimization, 39(3), 459–471.MathSciNetCrossRefMATH Karaboga, D., & Basturk, B. (2007). A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm. Journal of Global Optimization, 39(3), 459–471.MathSciNetCrossRefMATH
19.
Zurück zum Zitat Karaboga, D., & Ozturk, C. (2010). Fuzzy clustering with artificial bee colony algorithm. Scientific Research and Essays, 5(14), 1899–1902. Karaboga, D., & Ozturk, C. (2010). Fuzzy clustering with artificial bee colony algorithm. Scientific Research and Essays, 5(14), 1899–1902.
20.
Zurück zum Zitat Karaboga, D., Gorkemli, B., Ozturk, C., & Karaboga, N. (2014). A comprehensive survey: Artificial bee colony (ABC) algorithm and applications. Artificial Intelligence Revolution, 42(1), 21–57.CrossRef Karaboga, D., Gorkemli, B., Ozturk, C., & Karaboga, N. (2014). A comprehensive survey: Artificial bee colony (ABC) algorithm and applications. Artificial Intelligence Revolution, 42(1), 21–57.CrossRef
21.
Zurück zum Zitat Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks, 4, 1942–1948.CrossRef Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks, 4, 1942–1948.CrossRef
22.
Zurück zum Zitat Kulkarni, R. V., & Venayagamoorthy, G. K. (2010). Bio-inspired algorithms for autonomous deployment and localization of sensor nodes. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 40(6), 663–675.CrossRef Kulkarni, R. V., & Venayagamoorthy, G. K. (2010). Bio-inspired algorithms for autonomous deployment and localization of sensor nodes. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 40(6), 663–675.CrossRef
23.
Zurück zum Zitat Kulkarni, R. V., & Venayagamoorthy, G. K. (2011). Particle swarm optimization in wireless-sensor networks: A brief survey. Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(2), 262–267.CrossRef Kulkarni, R. V., & Venayagamoorthy, G. K. (2011). Particle swarm optimization in wireless-sensor networks: A brief survey. Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(2), 262–267.CrossRef
24.
Zurück zum Zitat Kulkarni, R. V., Venayagamoorthy, G. K., & Cheng, M. X. (2009). Bio-inspired node localization in wireless sensor networks. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (pp. 205–210). Kulkarni, R. V., Venayagamoorthy, G. K., & Cheng, M. X. (2009). Bio-inspired node localization in wireless sensor networks. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (pp. 205–210).
25.
Zurück zum Zitat Kulkarni, R. V., Förster, A., & Venayagamoorthy, G. K. (2011). Computational intelligence in wireless sensor networks: A survey. IEEE Communications Surveys and Tutorials, 13(1), 68–96.CrossRef Kulkarni, R. V., Förster, A., & Venayagamoorthy, G. K. (2011). Computational intelligence in wireless sensor networks: A survey. IEEE Communications Surveys and Tutorials, 13(1), 68–96.CrossRef
26.
Zurück zum Zitat Kulkarni, V. R., Desai, V., & Kulkarni, R. V. (2016). Multistage localization in wireless sensor networks using artificial bee colony algorithm. In Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1–8). Kulkarni, V. R., Desai, V., & Kulkarni, R. V. (2016). Multistage localization in wireless sensor networks using artificial bee colony algorithm. In Proceedings of the IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1–8).
27.
Zurück zum Zitat Li, H., Xiong, S., Liu, Y., Kou, J., & Duan, P. (2011). A localization algorithm in wireless sensor networks based on PSO. In Proceedings of the International Conference on Advances in Swarm Intelligence, Part II (pp. 200–206). Berlin: Springer. Li, H., Xiong, S., Liu, Y., Kou, J., & Duan, P. (2011). A localization algorithm in wireless sensor networks based on PSO. In Proceedings of the International Conference on Advances in Swarm Intelligence, Part II (pp. 200–206). Berlin: Springer.
28.
Zurück zum Zitat Ma, M., Liang, H., Jian, Guo M., Fan, Y., & Yin, Y. (2011). SAR image segmentation based on artificial bee colony algorithm. Appllied Soft Computing, 11(8), 5205–5214.CrossRef Ma, M., Liang, H., Jian, Guo M., Fan, Y., & Yin, Y. (2011). SAR image segmentation based on artificial bee colony algorithm. Appllied Soft Computing, 11(8), 5205–5214.CrossRef
29.
Zurück zum Zitat Mao, G., & Fidan, B. (2009). Localization algorithms and strategies for wireless sensor networks. Hershey, PA: Information Science Reference - Imprint of: IGI Publishing.CrossRef Mao, G., & Fidan, B. (2009). Localization algorithms and strategies for wireless sensor networks. Hershey, PA: Information Science Reference - Imprint of: IGI Publishing.CrossRef
30.
Zurück zum Zitat 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 (pp. 50–61). 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 (pp. 50–61).
31.
Zurück zum Zitat Niculescu, D., & Nath, B. (2001). Ad hoc positioning system (APS). Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), 5, 2926–2931.CrossRef Niculescu, D., & Nath, B. (2001). Ad hoc positioning system (APS). Proceedings of IEEE Global Telecommunications Conference (GLOBECOM), 5, 2926–2931.CrossRef
32.
Zurück zum Zitat Niculescu, D., & Nath, B. (2003). Ad hoc positioning system (APS) using AOA. In Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM) (Vol. 3, pp. 1734–1743). Niculescu, D., & Nath, B. (2003). Ad hoc positioning system (APS) using AOA. In Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM) (Vol. 3, pp. 1734–1743).
33.
Zurück zum Zitat Oliveto, P. S., He, J., & Yao, X. (2007). Time complexity of evolutionary algorithms for combinatorial optimization: A decade of results. International Journal of Automation and Computing, 4(3), 281–293.CrossRef Oliveto, P. S., He, J., & Yao, X. (2007). Time complexity of evolutionary algorithms for combinatorial optimization: A decade of results. International Journal of Automation and Computing, 4(3), 281–293.CrossRef
34.
Zurück zum Zitat Ong, Y.-S., Zhu, N., Lim, M.-H., & Wong, K. W. (2006). Classification of adaptive memetic algorithms: A comparative study. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 36(1), 141–152.CrossRef Ong, Y.-S., Zhu, N., Lim, M.-H., & Wong, K. W. (2006). Classification of adaptive memetic algorithms: A comparative study. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 36(1), 141–152.CrossRef
35.
Zurück zum Zitat Öztürk, C., Karaboğa, D., & Görkemlı, B. (2012). Artificial bee colony algorithm for dynamic deployment of wireless sensor networks. Turkish Journal of Electrical Engineering & Computer Sciences, 20(2), 255–262. Öztürk, C., Karaboğa, D., & Görkemlı, B. (2012). Artificial bee colony algorithm for dynamic deployment of wireless sensor networks. Turkish Journal of Electrical Engineering & Computer Sciences, 20(2), 255–262.
36.
Zurück zum Zitat Patwari, N., Ash, J. N., Kyperountas, S., Hero, A. O., Moses, R. L., & Correal, N. S. (2005). Locating the nodes: Cooperative localization in wireless sensor networks. IEEE Signal Processing Magazine, 22(4), 54–69.CrossRef Patwari, N., Ash, J. N., Kyperountas, S., Hero, A. O., Moses, R. L., & Correal, N. S. (2005). Locating the nodes: Cooperative localization in wireless sensor networks. IEEE Signal Processing Magazine, 22(4), 54–69.CrossRef
37.
Zurück zum Zitat Peng, R., & Sichitiu, M. L. (2007). Probabilistic localization for outdoor wireless sensor networks. SIGMOBILE Mobile Compution and Communication Review, 11(1), 53–64.CrossRef Peng, R., & Sichitiu, M. L. (2007). Probabilistic localization for outdoor wireless sensor networks. SIGMOBILE Mobile Compution and Communication Review, 11(1), 53–64.CrossRef
38.
Zurück zum Zitat Priyantha, N. B., Balakrishnan, H., Demaine, E., & Teller, S. (2003). Poster abstract: Anchor-free distributed localization in sensor networks. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (pp. 340–341). Priyantha, N. B., Balakrishnan, H., Demaine, E., & Teller, S. (2003). Poster abstract: Anchor-free distributed localization in sensor networks. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems (pp. 340–341).
39.
Zurück zum Zitat Savarese, C., Rabaey, J., & Langendoen, K. (2002). Robust positioning algorithms for distributed ad-hoc wireless sensor networks. In Proceedings of the USENIX Technical Annual Conference (pp. 317–327). Savarese, C., Rabaey, J., & Langendoen, K. (2002). Robust positioning algorithms for distributed ad-hoc wireless sensor networks. In Proceedings of the USENIX Technical Annual Conference (pp. 317–327).
40.
Zurück zum Zitat Savvides, A., Han, C. C., & Strivastava, M. B. (2001). Dynamic fine-grained localization in ad-hoc networks of sensors. In Proceedings of the 7th Annual International Conference on Mobile Computing and Networking (MobiCom), New York, NY, USA (pp. 166–179). Savvides, A., Han, C. C., & Strivastava, M. B. (2001). Dynamic fine-grained localization in ad-hoc networks of sensors. In Proceedings of the 7th Annual International Conference on Mobile Computing and Networking (MobiCom), New York, NY, USA (pp. 166–179).
41.
Zurück zum Zitat Udgata, S. K., Sabat, S. L., & Mini, S. (2009). Sensor deployment in irregular terrain using artificial bee colony algorithm. In World Congress on Nature Biologically Inspired Computing, NaBIC 2009 (pp. 1309–1314). Udgata, S. K., Sabat, S. L., & Mini, S. (2009). Sensor deployment in irregular terrain using artificial bee colony algorithm. In World Congress on Nature Biologically Inspired Computing, NaBIC 2009 (pp. 1309–1314).
42.
Zurück zum Zitat Vargas Benítez, C. M., & Lopes, H. S. (2010). Parallel artificial bee colony algorithm approaches for protein structure prediction using the 3DHP-SC model. In Intelligent Distributed Computing IV: Proceedings of the 4th International Symposium on Intelligent Distributed Computing, Tangier, Morocco. Berlin: Springer (pp. 255–264). Vargas Benítez, C. M., & Lopes, H. S. (2010). Parallel artificial bee colony algorithm approaches for protein structure prediction using the 3DHP-SC model. In Intelligent Distributed Computing IV: Proceedings of the 4th International Symposium on Intelligent Distributed Computing, Tangier, Morocco. Berlin: Springer (pp. 255–264).
43.
Zurück zum Zitat Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292–2330.CrossRef Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292–2330.CrossRef
44.
Zurück zum Zitat Youssef, M., Youssef, A., Rieger, C., Shankar, U., & Agrawala, A. (2006). Pinpoint: An asynchronous time-based location determination system. In Proceedings of the 4th International Conference on Mobile Systems, Applications and Services (MobiSys) (pp. 165–176). New York, NY: ACM. Youssef, M., Youssef, A., Rieger, C., Shankar, U., & Agrawala, A. (2006). Pinpoint: An asynchronous time-based location determination system. In Proceedings of the 4th International Conference on Mobile Systems, Applications and Services (MobiSys) (pp. 165–176). New York, NY: ACM.
45.
Zurück zum Zitat Zhao, H., Pei, Z., Jiang, J., Guan, R., Wang, C., & Shi, X. (2010). A hybrid swarm intelligent method based on genetic algorithm and artificial bee colony. In Proceedings of the First International Conference, Advances in Swarm Intelligence (ICSI) (pp. 558–565). Berlin: Springer. Zhao, H., Pei, Z., Jiang, J., Guan, R., Wang, C., & Shi, X. (2010). A hybrid swarm intelligent method based on genetic algorithm and artificial bee colony. In Proceedings of the First International Conference, Advances in Swarm Intelligence (ICSI) (pp. 558–565). Berlin: Springer.
Metadaten
Titel
A comparative investigation of deterministic and metaheuristic algorithms for node localization in wireless sensor networks
verfasst von
Vaishali R. Kulkarni
Veena Desai
Raghavendra V. Kulkarni
Publikationsdatum
26.04.2019
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 5/2019
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-019-01994-9

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