Skip to main content
Top
Published in: Wireless Networks 5/2019

26-04-2019

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

Authors: Vaishali R. Kulkarni, Veena Desai, Raghavendra V. Kulkarni

Published in: Wireless Networks | Issue 5/2019

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

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.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
go back to reference 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.
Metadata
Title
A comparative investigation of deterministic and metaheuristic algorithms for node localization in wireless sensor networks
Authors
Vaishali R. Kulkarni
Veena Desai
Raghavendra V. Kulkarni
Publication date
26-04-2019
Publisher
Springer US
Published in
Wireless Networks / Issue 5/2019
Print ISSN: 1022-0038
Electronic ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-019-01994-9

Other articles of this Issue 5/2019

Wireless Networks 5/2019 Go to the issue