Skip to main content
Top
Published in: Wireless Personal Communications 1/2021

07-08-2020

An Energy Efficient Clustered Gravitational and Fuzzy Based Routing Algorithm in WSNs

Authors: Munuswamy Selvi, S. V. N. Santhosh Kumar, Sannasi Ganapathy, Ayyasamy Ayyanar, Harichandran Khanna Nehemiah, Arputharaj Kannan

Published in: Wireless Personal Communications | Issue 1/2021

Log in

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

search-config
loading …

Abstract

Wireless sensor networks consist of many tiny sensor nodes which are deployed in various geographical locations for sensing the normal spectacles and also to transmit the collected information to the base station which is also named destination node through multiple nodes present in the network. Most of the existing heuristics algorithms used for finding the optimal routes have limitations in the provision of effective solutions for routing and clustering mechanisms in larger search spaces. Hence, when the search space increases exponentially, the chance of creating the optimal solution for clustering and routing is decreasing and ultimately an un-optimized process depletes the sensor node resources. In order to address the challenges and limitations present in the existing routing systems, two new heuristics algorithms namely gravitational approach based clustering method and a clustered gravitational routing algorithm have been proposed in this paper for providing an optimal solution for efficient clustering and effective routing. Moreover, a fuzzy logic based deductive inference system has been designed and used in this work for selecting the most appropriate nodes as cluster head nodes from the nodes present in each cluster. The simulation results obtained from this work show that the clustering accuracy and the network lifetime are increased and the energy consumption as well as delay are reduced with the application of these proposed algorithms.

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

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+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 "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 Shafiq, M., Ashraf, H., Ullah, A., & Tahira, S. (2020). Systematic literature review on energy efficient routing schemes in WSN—A survey. Mobile Network Applications, 25, 882–895. Shafiq, M., Ashraf, H., Ullah, A., & Tahira, S. (2020). Systematic literature review on energy efficient routing schemes in WSN—A survey. Mobile Network Applications, 25, 882–895.
2.
go back to reference He, W. (2019). Energy-saving algorithm and simulation of wireless sensor networks based on clustering routing protocol. IEEE Access, 7, 172505–172514. He, W. (2019). Energy-saving algorithm and simulation of wireless sensor networks based on clustering routing protocol. IEEE Access, 7, 172505–172514.
3.
go back to reference Shivappa, N., & Manvi, S. S. (2019). Fuzzy-based cluster head selection and cluster formation in wireless sensor networks. IET Networks, 8(6), 390–397. Shivappa, N., & Manvi, S. S. (2019). Fuzzy-based cluster head selection and cluster formation in wireless sensor networks. IET Networks, 8(6), 390–397.
4.
go back to reference El Alami, H., & Najid, A. (2019). ECH: An enhanced clustering hierarchy approach to maximize lifetime of wireless sensor networks. IEEE Access, 7, 107142–107153. El Alami, H., & Najid, A. (2019). ECH: An enhanced clustering hierarchy approach to maximize lifetime of wireless sensor networks. IEEE Access, 7, 107142–107153.
5.
go back to reference Selvi, M., Thangaramya, K., Ganapathy, S., Kulothungan, K., Khannah Nehemiah, H., & Kannan, A. (2019). An energy aware trust based secure routing algorithm for effective communication in wireless sensor networks. Wireless Personal Communications, 105(4), 1475–1490. Selvi, M., Thangaramya, K., Ganapathy, S., Kulothungan, K., Khannah Nehemiah, H., & Kannan, A. (2019). An energy aware trust based secure routing algorithm for effective communication in wireless sensor networks. Wireless Personal Communications, 105(4), 1475–1490.
6.
go back to reference Priya, S., Tamizharasan, P. S., & Kannan, A. (2019). Fuzzy genetic elliptic curve Diffie Hellman algorithm for secured communication in networks. Wireless Personal Communications, 105(3), 993–1007. Priya, S., Tamizharasan, P. S., & Kannan, A. (2019). Fuzzy genetic elliptic curve Diffie Hellman algorithm for secured communication in networks. Wireless Personal Communications, 105(3), 993–1007.
7.
go back to reference Ogundile, O. O., Balogun, M. B., Ijiga, O. E., & Falayi, E. O. (2019). Energy-balanced and energy-efficient clustering routing protocol for wireless sensor networks. IET Communications, 13(10), 1449–1457. Ogundile, O. O., Balogun, M. B., Ijiga, O. E., & Falayi, E. O. (2019). Energy-balanced and energy-efficient clustering routing protocol for wireless sensor networks. IET Communications, 13(10), 1449–1457.
8.
go back to reference Nancy, P., Muthurajkumar, S., Ganapathy, S., Santhosh Kumar, S. V. N., Selvi, M., & Kannan, A. (2020). Intrusion detection using dynamic feature selection and fuzzy temporal decision tree classification for wireless sensor networks. IET Communications, 14(5), 888–895. Nancy, P., Muthurajkumar, S., Ganapathy, S., Santhosh Kumar, S. V. N., Selvi, M., & Kannan, A. (2020). Intrusion detection using dynamic feature selection and fuzzy temporal decision tree classification for wireless sensor networks. IET Communications, 14(5), 888–895.
9.
go back to reference Beheshtiasl, A., & Ghafari, A. (2019). Secure and trust-aware routing scheme in wireless sensor networks. Wireless Personal Communications, 107, 1799–1814. Beheshtiasl, A., & Ghafari, A. (2019). Secure and trust-aware routing scheme in wireless sensor networks. Wireless Personal Communications, 107, 1799–1814.
10.
go back to reference Jain, A., & Ashok Kumar, G. (2020). Energy efficient fuzzy routing protocol for wireless sensor networks. Wireless Personal Communications, 110, 1459–1474. Jain, A., & Ashok Kumar, G. (2020). Energy efficient fuzzy routing protocol for wireless sensor networks. Wireless Personal Communications, 110, 1459–1474.
11.
go back to reference Mazinani, A., Mazinani, S. M., & Mirzaie, M. (2019). FMCR-CT: An energy-efficient fuzzy multi cluster-based routing with a constant threshold in wireless sensor network. Alexandria Engineering Journal, 58(1), 127–141. Mazinani, A., Mazinani, S. M., & Mirzaie, M. (2019). FMCR-CT: An energy-efficient fuzzy multi cluster-based routing with a constant threshold in wireless sensor network. Alexandria Engineering Journal, 58(1), 127–141.
12.
go back to reference Logambigai, R., & Kannan, A. (2016). Fuzzy logic based unequal clustering for wireless sensor networks. Wireless Networks, 22, 945–957. Logambigai, R., & Kannan, A. (2016). Fuzzy logic based unequal clustering for wireless sensor networks. Wireless Networks, 22, 945–957.
13.
go back to reference Kundu, S. (1999). Gravitational clustering: A new approach based on the spatial distribution of the points. Journal of Pattern Recognition, 32, 1149–1160. Kundu, S. (1999). Gravitational clustering: A new approach based on the spatial distribution of the points. Journal of Pattern Recognition, 32, 1149–1160.
14.
go back to reference Selvi, M., Logambigai, R., Ganapathy, S., Sai Ramesh, L., Khanna Nehemiah, H., & Kannan, A. (2006). Fuzzy temporal approach for energy efficient routing in WSN. In Proceedings of the international conference on informatics and analytics (pp. 1–5). ACM. Selvi, M., Logambigai, R., Ganapathy, S., Sai Ramesh, L., Khanna Nehemiah, H., & Kannan, A. (2006). Fuzzy temporal approach for energy efficient routing in WSN. In Proceedings of the international conference on informatics and analytics (pp. 1–5). ACM.
15.
go back to reference Bitam, S., Mellouk, A., & Zeadally, S. (2015). Bio-inspired routing algorithms survey for vehicular ad hoc networks. IEEE Communication Surveys and Tutorials, 17(2), 843–867. Bitam, S., Mellouk, A., & Zeadally, S. (2015). Bio-inspired routing algorithms survey for vehicular ad hoc networks. IEEE Communication Surveys and Tutorials, 17(2), 843–867.
16.
go back to reference Bagci, H., & Yazici, A. (2013). An energy aware fuzzy approach to unequal clustering in wireless sensor networks. Applied Soft Computing, 13(4), 1741–1749. Bagci, H., & Yazici, A. (2013). An energy aware fuzzy approach to unequal clustering in wireless sensor networks. Applied Soft Computing, 13(4), 1741–1749.
17.
go back to reference Chi, Y. P., & Chang, H. P. (2013). An energy-aware grid-based routing scheme for wireless sensor networks. Telecommunication Systems, 54(4), 403–415. Chi, Y. P., & Chang, H. P. (2013). An energy-aware grid-based routing scheme for wireless sensor networks. Telecommunication Systems, 54(4), 403–415.
18.
go back to reference Selvi, M., Velvizhy, P., Ganapathy, S., Khanna-Nehemiah, H., & Kannan, A. (2019). A rule based delay constrained energy efficient routing technique for wireless sensor networks. Cluster Computing, 22(5), 10839–10848. Selvi, M., Velvizhy, P., Ganapathy, S., Khanna-Nehemiah, H., & Kannan, A. (2019). A rule based delay constrained energy efficient routing technique for wireless sensor networks. Cluster Computing, 22(5), 10839–10848.
19.
go back to reference Selvi, M., Logambigai, R., Ganapathy, S., Khanna Nehemiah, H., & Kannan, A. (2017). An intelligent agent and FSO based efficient routing algorithm for wireless sensor network. In Proceedings of the second international conference on recent trends and challenges in computational models (ICRTCCM) (pp. 100–105). IEEE. Selvi, M., Logambigai, R., Ganapathy, S., Khanna Nehemiah, H., & Kannan, A. (2017). An intelligent agent and FSO based efficient routing algorithm for wireless sensor network. In Proceedings of the second international conference on recent trends and challenges in computational models (ICRTCCM) (pp. 100–105). IEEE.
20.
go back to reference Logambigai, R., Ganapathy, S., & Kannan, A. (2018). Energy-efficient grid-based routing algorithm using intelligent fuzzy rules for wireless sensor networks. Computers & Electrical Engineering, 68, 62–75. Logambigai, R., Ganapathy, S., & Kannan, A. (2018). Energy-efficient grid-based routing algorithm using intelligent fuzzy rules for wireless sensor networks. Computers & Electrical Engineering, 68, 62–75.
21.
go back to reference Kalidoss, T., Rajasekaran, L., Kanagasabai, K., Ganapathy, S., & Kannan, A. (2020). QoS aware trust based routing algorithm for wireless sensor networks. Wireless Personal Communications, 110(4), 1637–1658. Kalidoss, T., Rajasekaran, L., Kanagasabai, K., Ganapathy, S., & Kannan, A. (2020). QoS aware trust based routing algorithm for wireless sensor networks. Wireless Personal Communications, 110(4), 1637–1658.
22.
go back to reference Hua, E. Y., & Haas, Z. J. (2015). Mobile-projected trajectory algorithm with velocity-change detection for predicting residual link lifetime in MANET. IEEE Transactions on Vehicular Technology, 64(3), 1065–1078. Hua, E. Y., & Haas, Z. J. (2015). Mobile-projected trajectory algorithm with velocity-change detection for predicting residual link lifetime in MANET. IEEE Transactions on Vehicular Technology, 64(3), 1065–1078.
23.
go back to reference Tsai, C.-W., Hong, T.-P., & Shiu, G.-N. (2016). Metaheuristics for the lifetime of WSN: A review. IEEE Sensors Journal, 16(9), 2812–2831. Tsai, C.-W., Hong, T.-P., & Shiu, G.-N. (2016). Metaheuristics for the lifetime of WSN: A review. IEEE Sensors Journal, 16(9), 2812–2831.
24.
go back to reference Zahedi, Z. M., Akbari, R., Shokouhifar, M., Safaei, F., & Jalali, A. (2016). Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks. Expert Systems with Applications, 55, 313–328. Zahedi, Z. M., Akbari, R., Shokouhifar, M., Safaei, F., & Jalali, A. (2016). Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks. Expert Systems with Applications, 55, 313–328.
25.
go back to reference Chen, Y., & Yang, H. (2016). Sparse modeling and recursive prediction of space–time dynamics in stochastic sensor networks. IEEE Transactions on Automation Science and Engineering, 13(1), 215–226. Chen, Y., & Yang, H. (2016). Sparse modeling and recursive prediction of space–time dynamics in stochastic sensor networks. IEEE Transactions on Automation Science and Engineering, 13(1), 215–226.
26.
go back to reference Sarma, H. K. D., Mall, R., & Kar, A. (2016). E2R2: Energy-efficient and reliable routing for mobile wireless sensor networks. IEEE Systems Journal, 10(2), 604–616. Sarma, H. K. D., Mall, R., & Kar, A. (2016). E2R2: Energy-efficient and reliable routing for mobile wireless sensor networks. IEEE Systems Journal, 10(2), 604–616.
27.
go back to reference Xie, G., & Pan, F. (2016). Cluster-based routing for the mobile sink in wireless sensor networks with obstacles. Special section on green communications and networking for 5G wireless. IEEE Access, 4, 2019–2028. Xie, G., & Pan, F. (2016). Cluster-based routing for the mobile sink in wireless sensor networks with obstacles. Special section on green communications and networking for 5G wireless. IEEE Access, 4, 2019–2028.
28.
go back to reference Tan, L., & Mou, W. (2016). Data reduction in wireless sensor networks: A hierarchical LMS prediction approach. IEEE Sensors Journal, 16(6), 1708–1715. Tan, L., & Mou, W. (2016). Data reduction in wireless sensor networks: A hierarchical LMS prediction approach. IEEE Sensors Journal, 16(6), 1708–1715.
29.
go back to reference Ari, A. A. A., Yenke, B. O., Labraoui, N., Damakoa, I., & Gueroui, A. (2016). A power efficient cluster-based routing algorithm for wireless sensor networks: Honey bees swarm intelligence based approach. Journal of Network and Computer Applications, 69, 77–97. Ari, A. A. A., Yenke, B. O., Labraoui, N., Damakoa, I., & Gueroui, A. (2016). A power efficient cluster-based routing algorithm for wireless sensor networks: Honey bees swarm intelligence based approach. Journal of Network and Computer Applications, 69, 77–97.
30.
go back to reference Machado, R., Zhang, W., Wang, G., & Tekinay, S. (2010). Coverage properties of clustered wireless sensor networks. ACM Transactions on Sensor Networks, 7(2), 1–21. Machado, R., Zhang, W., Wang, G., & Tekinay, S. (2010). Coverage properties of clustered wireless sensor networks. ACM Transactions on Sensor Networks, 7(2), 1–21.
31.
go back to reference Bajaber, F., & Awan, I. (2014). An efficient cluster-based communication protocol for wireless sensor networks. Telecommunication System, 55, 387–401. Bajaber, F., & Awan, I. (2014). An efficient cluster-based communication protocol for wireless sensor networks. Telecommunication System, 55, 387–401.
32.
go back to reference Nayak, P., & Devulapalli, A. (2016). A fuzzy logic-based clustering algorithm for WSN to extend the network lifetime. IEEE Sensors Journal, 16(1), 137–144. Nayak, P., & Devulapalli, A. (2016). A fuzzy logic-based clustering algorithm for WSN to extend the network lifetime. IEEE Sensors Journal, 16(1), 137–144.
33.
go back to reference Raza, U., Camerra, A., Murphy, A. L., Palpanas, T., & Picco, G. P. (2015). Practical data prediction for real-world wireless sensor networks. IEEE Transactions on Knowledge and Data Engineering, 27(8), 2231–2244. Raza, U., Camerra, A., Murphy, A. L., Palpanas, T., & Picco, G. P. (2015). Practical data prediction for real-world wireless sensor networks. IEEE Transactions on Knowledge and Data Engineering, 27(8), 2231–2244.
34.
go back to reference Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the thirty-third IEEE annual Hawaii international conference on system sciences (pp. 1–10). Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the thirty-third IEEE annual Hawaii international conference on system sciences (pp. 1–10).
35.
go back to reference Mishra, P., & Dhyani, A. (2015). Proposed framework of LEACH protocol with location based cluster head selection. International Journal of Electronics and Communication Technology, 6(3), 38–40. Mishra, P., & Dhyani, A. (2015). Proposed framework of LEACH protocol with location based cluster head selection. International Journal of Electronics and Communication Technology, 6(3), 38–40.
36.
go back to reference Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3(4), 366–379. Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3(4), 366–379.
37.
go back to reference El-Said, S. A., Osamaa, A., & Hassanien, A. E. (2016). Optimized hierarchical routing technique for wireless sensors networks. Soft Computing, 20, 4549–4564. El-Said, S. A., Osamaa, A., & Hassanien, A. E. (2016). Optimized hierarchical routing technique for wireless sensors networks. Soft Computing, 20, 4549–4564.
38.
go back to reference Thangaramya, K., Kulothungan, K., Logambigai, R., Selvi, M., Ganapathy, S., & Kannan, A. (2019). Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT. Computer Networks, 151, 211–223. Thangaramya, K., Kulothungan, K., Logambigai, R., Selvi, M., Ganapathy, S., & Kannan, A. (2019). Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT. Computer Networks, 151, 211–223.
39.
go back to reference Han, G., Jiang, J., Guizani, M., & Rodrigues, J. J. C. (2016). Green routing protocols for wireless multimedia sensor networks. IEEE Wireless Communications, 23, 140–146. Han, G., Jiang, J., Guizani, M., & Rodrigues, J. J. C. (2016). Green routing protocols for wireless multimedia sensor networks. IEEE Wireless Communications, 23, 140–146.
40.
go back to reference Pursley, M. B., Russell, H. B., & Staples, P. E. (1999). Routing for multimedia traffic in wireless frequency-hop communication networks. IEEE Journal on Selected Areas in Communications, 17(5), 784–792. Pursley, M. B., Russell, H. B., & Staples, P. E. (1999). Routing for multimedia traffic in wireless frequency-hop communication networks. IEEE Journal on Selected Areas in Communications, 17(5), 784–792.
41.
go back to reference Lin, K., Rodrigues, J. J. C., Ge, H., Xiong, N., & Liang, X. (2011). Energy efficiency QoS assurance routing in wireless multimedia sensor networks. IEEE Systems Journal, 5(4), 495–505. Lin, K., Rodrigues, J. J. C., Ge, H., Xiong, N., & Liang, X. (2011). Energy efficiency QoS assurance routing in wireless multimedia sensor networks. IEEE Systems Journal, 5(4), 495–505.
42.
go back to reference Xu, H., Huang, L., Qiao, C., Zhang, Y., & Sun, Q. (2012). Bandwidth-power aware cooperative multipath routing for wireless multimedia sensor networks. IEEE Transactions on Wireless Communications, 11(4), 1532–1543. Xu, H., Huang, L., Qiao, C., Zhang, Y., & Sun, Q. (2012). Bandwidth-power aware cooperative multipath routing for wireless multimedia sensor networks. IEEE Transactions on Wireless Communications, 11(4), 1532–1543.
43.
go back to reference Pantazis, N. A., Nikolidakis, S. A., & Vergados, D. D. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communications Surveys and Tutorials, 15(2), 551–591. Pantazis, N. A., Nikolidakis, S. A., & Vergados, D. D. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communications Surveys and Tutorials, 15(2), 551–591.
44.
go back to reference Kabir, M. H., Mukhtaruzzaman, M., & Atiquzzaman, M. (2013). Efficient route optimization scheme for nested-NEMO. Journal of Network and Computer Applications, 36, 1039–1049. Kabir, M. H., Mukhtaruzzaman, M., & Atiquzzaman, M. (2013). Efficient route optimization scheme for nested-NEMO. Journal of Network and Computer Applications, 36, 1039–1049.
45.
go back to reference Tyagi, S., & Kumar, N. (2013). A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks. Journal of Network and Computer Applications, 36, 623–645. Tyagi, S., & Kumar, N. (2013). A systematic review on clustering and routing techniques based upon LEACH protocol for wireless sensor networks. Journal of Network and Computer Applications, 36, 623–645.
46.
go back to reference Zungeru, A. M., Ang, L.-M., & Seng, K. P. (2012). Classical and swarm intelligence based routing protocols for wireless sensor networks: A survey and comparison. Journal of Network and Computer Applications, 35, 1508–1536. Zungeru, A. M., Ang, L.-M., & Seng, K. P. (2012). Classical and swarm intelligence based routing protocols for wireless sensor networks: A survey and comparison. Journal of Network and Computer Applications, 35, 1508–1536.
47.
go back to reference Papadopoulos, A., Navarra, A., McCann, J. A., & Pinotti, C. M. (2012). VIBE: an energy efficient routing protocol for dense and mobile sensor networks. Journal of Network and Computer Applications, 35(4), 1177–1190. Papadopoulos, A., Navarra, A., McCann, J. A., & Pinotti, C. M. (2012). VIBE: an energy efficient routing protocol for dense and mobile sensor networks. Journal of Network and Computer Applications, 35(4), 1177–1190.
48.
go back to reference Senouci, M. R., Mellouk, A., Senoucid, H., & Aissani, A. (2012). Performance evaluation of network lifetime spatial–temporal distribution for WSN routing protocols. Journal of Network and Computer Applications, 35(4), 1317–1328. Senouci, M. R., Mellouk, A., Senoucid, H., & Aissani, A. (2012). Performance evaluation of network lifetime spatial–temporal distribution for WSN routing protocols. Journal of Network and Computer Applications, 35(4), 1317–1328.
49.
go back to reference Mottola, L. (2011). Programming wireless sensor networks: Fundamental concepts and state of the art. Journal ACM Computing Surveys CSUR Surveys, 43(3), 1–51. Mottola, L. (2011). Programming wireless sensor networks: Fundamental concepts and state of the art. Journal ACM Computing Surveys CSUR Surveys, 43(3), 1–51.
50.
go back to reference Rashedi, E., Nezamabadi-pour, H., & Saryazdi, S. (2009). GSA: A gravitational search algorithm. Information Sciences, 179, 2232–2248.MATH Rashedi, E., Nezamabadi-pour, H., & Saryazdi, S. (2009). GSA: A gravitational search algorithm. Information Sciences, 179, 2232–2248.MATH
Metadata
Title
An Energy Efficient Clustered Gravitational and Fuzzy Based Routing Algorithm in WSNs
Authors
Munuswamy Selvi
S. V. N. Santhosh Kumar
Sannasi Ganapathy
Ayyasamy Ayyanar
Harichandran Khanna Nehemiah
Arputharaj Kannan
Publication date
07-08-2020
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 1/2021
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07705-4

Other articles of this Issue 1/2021

Wireless Personal Communications 1/2021 Go to the issue