Skip to main content
Erschienen in: Wireless Networks 4/2021

05.04.2021

A hybridization strategy using equal and unequal clustering schemes to mitigate idle listening for lifetime maximization of wireless sensor network

verfasst von: Nura Modi Shagari, Mohd Yamani Idna Idris, Rosli Bin Salleh, Ismail Ahmedy, Ghulam Murtaza, Aznul Qalid Bin Md Sabri

Erschienen in: Wireless Networks | Ausgabe 4/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The main focus in the designing of wireless sensor networks (WSNs) applications and protocols is minimizing energy dissipation while at the same time maximizing the network lifetime. In this paper, we investigate the idle listening and hotspot problems with respect to the clustering routing technique in WSNs. Some of the studies in clustering centered around equal clustering scheme while others were based on unequal clustering scheme. Equal clustering scheme avoids inter-cluster idle listening as the intra-cluster data collection can be completed at the same time across all clusters in the network but lead to hotspot problem due to additional traffic relay experienced by cluster heads near the base station. Similarly, unequal clustering addresses hotspot problem but lead to inter-cluster idle listening due to the use of global network-wide intra-cluster collection among clusters of unequal sizes and densities. In this paper we proposed a zone-based clustering scheme referred to as hybrid equal and unequal clustering (HEUC) that jointly address inter-cluster idle listening and hotspot problems to maximize the lifetime of WSNs. To achieve this, the network area is firstly partitioned into zones. The size of clusters in the same zone is designed to be equal and cluster size increases across zones as the distance from the BS increases. Secondly, the density of nodes deployed in each cluster per zone is obtained in such a way that the distribution of nodes in zones away from BS increases according to the radius increase in clusters across the zones. Thirdly, a deterministic deployment strategy is used to deploy nodes into various clusters. Fourthly, we implement a zone-wise intra-cluster data collection strategy that allows intra-cluster data collection to be completed at once to address inter-cluster idle listening. Lastly, a multihop routing is used for data forwarding to BS. The result shows that our proposed HEUC has 38% and 51% lifetime improvement against EBULRP and AECR respectively.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Literatur
1.
Zurück zum Zitat Shaikh, F. K., Zeadally, S., & Exposito, E. (2015). Enabling technologies for green internet of things. IEEE Systems Journal, 11(2), 983–994.CrossRef Shaikh, F. K., Zeadally, S., & Exposito, E. (2015). Enabling technologies for green internet of things. IEEE Systems Journal, 11(2), 983–994.CrossRef
2.
Zurück zum Zitat Adil Mahdi, O., Abdul Wahab, A. W., Idris, M. Y. I., Abu Znaid, A., Al-Mayouf, Y. R. B., & Khan, S. (2016). WDARS: A weighted data aggregation routing strategy with minimum link cost in event-driven WSNs. Journal of Sensors. https://doi.org/10.1155/2016/3428730. Adil Mahdi, O., Abdul Wahab, A. W., Idris, M. Y. I., Abu Znaid, A., Al-Mayouf, Y. R. B., & Khan, S. (2016). WDARS: A weighted data aggregation routing strategy with minimum link cost in event-driven WSNs. Journal of Sensors. https://​doi.​org/​10.​1155/​2016/​3428730.
3.
Zurück zum Zitat Arampatzis, T., Lygeros, J., & Manesis, S. (2005). A survey of applications of wireless sensors and wireless sensor networks. In Proceedings of the 2005 IEEE international symposium on, Mediterrean conference on control and automation intelligent control. IEEE (pp. 719–724). Arampatzis, T., Lygeros, J., & Manesis, S. (2005). A survey of applications of wireless sensors and wireless sensor networks. In Proceedings of the 2005 IEEE international symposium on, Mediterrean conference on control and automation intelligent control. IEEE (pp. 719–724).
4.
Zurück zum Zitat Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.CrossRef Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.CrossRef
5.
Zurück zum Zitat Chen, G., Li, C., Ye, M., & Wu, J. (2009). An unequal cluster-based routing protocol in wireless sensor networks. Wireless Networks, 15(2), 193–207.CrossRef Chen, G., Li, C., Ye, M., & Wu, J. (2009). An unequal cluster-based routing protocol in wireless sensor networks. Wireless Networks, 15(2), 193–207.CrossRef
6.
Zurück zum Zitat Shagari, N. M., Idris, M. Y. I., Salleh, R. B., Ahmedy, I., Murtaza, G., & Shehadeh, H. A. (2020). Heterogeneous energy and traffic aware sleep-awake cluster-based routing protocol for wireless sensor network. IEEE Access, 8, 12232–12252.CrossRef Shagari, N. M., Idris, M. Y. I., Salleh, R. B., Ahmedy, I., Murtaza, G., & Shehadeh, H. A. (2020). Heterogeneous energy and traffic aware sleep-awake cluster-based routing protocol for wireless sensor network. IEEE Access, 8, 12232–12252.CrossRef
7.
Zurück zum Zitat Arjunan, S., & Pothula, S. (2019). A survey on unequal clustering protocols in wireless sensor networks. Journal of King Saud University-Computer and Information Sciences, 31(3), 304–317.CrossRef Arjunan, S., & Pothula, S. (2019). A survey on unequal clustering protocols in wireless sensor networks. Journal of King Saud University-Computer and Information Sciences, 31(3), 304–317.CrossRef
8.
Zurück zum Zitat Wu, Y., Li, X.-Y., Li, Y., & Lou, W. (2009). Energy-efficient wake-up scheduling for data collection and aggregation. IEEE Transactions on Parallel and Distributed Systems, 21(2), 275–287.CrossRef Wu, Y., Li, X.-Y., Li, Y., & Lou, W. (2009). Energy-efficient wake-up scheduling for data collection and aggregation. IEEE Transactions on Parallel and Distributed Systems, 21(2), 275–287.CrossRef
9.
Zurück zum Zitat Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 4, 366–379.CrossRef Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 4, 366–379.CrossRef
10.
Zurück zum Zitat Neamatollahi, P., Naghibzadeh, M., Abrishami, S., & Yaghmaee, M.-H. (2018). Distributed clustering-task scheduling for wireless sensor networks using dynamic hyper round policy. IEEE Transactions on Mobile Computing, 17(2), 334–347.CrossRef Neamatollahi, P., Naghibzadeh, M., Abrishami, S., & Yaghmaee, M.-H. (2018). Distributed clustering-task scheduling for wireless sensor networks using dynamic hyper round policy. IEEE Transactions on Mobile Computing, 17(2), 334–347.CrossRef
11.
Zurück zum Zitat Neamatollahi, P., Abrishami, S., Naghibzadeh, M., Moghaddam, M. H. Y., & Younis, O. (2018). Hierarchical clustering-task scheduling policy in cluster-based wireless sensor networks. IEEE Transactions on Industrial Informatics, 14(5), 1876–1886.CrossRef Neamatollahi, P., Abrishami, S., Naghibzadeh, M., Moghaddam, M. H. Y., & Younis, O. (2018). Hierarchical clustering-task scheduling policy in cluster-based wireless sensor networks. IEEE Transactions on Industrial Informatics, 14(5), 1876–1886.CrossRef
12.
Zurück zum Zitat Haseeb, K., Bakar, K. A., Abdullah, A. H., & Darwish, T. (2017). Adaptive energy aware cluster-based routing protocol for wireless sensor networks. Wireless Networks, 23(6), 1953–1966.CrossRef Haseeb, K., Bakar, K. A., Abdullah, A. H., & Darwish, T. (2017). Adaptive energy aware cluster-based routing protocol for wireless sensor networks. Wireless Networks, 23(6), 1953–1966.CrossRef
13.
Zurück zum Zitat Li, C., Ye, M., Chen, G., & Wu, J. (2005). An energy-efficient unequal clustering mechanism for wireless sensor networks. In IEEE international conference on mobile adhoc and sensor systems conference (pp. 8–604). IEEE. Li, C., Ye, M., Chen, G., & Wu, J. (2005). An energy-efficient unequal clustering mechanism for wireless sensor networks. In IEEE international conference on mobile adhoc and sensor systems conference (pp. 8–604). IEEE.
14.
Zurück zum Zitat Wang, T., Wang, Y., & Han, C. (2017). An improved clustering routing mechanism for wireless Ad hoc network. Journal of Intelligent & Fuzzy Systems, 32(5), 3401–3412.CrossRef Wang, T., Wang, Y., & Han, C. (2017). An improved clustering routing mechanism for wireless Ad hoc network. Journal of Intelligent & Fuzzy Systems, 32(5), 3401–3412.CrossRef
15.
Zurück zum Zitat Afsar, M. M., & Tayarani-N, M.-H. (2014). Clustering in sensor networks: A literature survey. Journal of Network and Computer Applications, 46, 198–226.CrossRef Afsar, M. M., & Tayarani-N, M.-H. (2014). Clustering in sensor networks: A literature survey. Journal of Network and Computer Applications, 46, 198–226.CrossRef
16.
Zurück zum Zitat Chen, H., Chi, K. T., & Feng, J. (2009). Impact of topology on performance and energy efficiency in wireless sensor networks for source extraction. IEEE Transactions on Parallel and Distributed Systems, 20(6), 886–897.CrossRef Chen, H., Chi, K. T., & Feng, J. (2009). Impact of topology on performance and energy efficiency in wireless sensor networks for source extraction. IEEE Transactions on Parallel and Distributed Systems, 20(6), 886–897.CrossRef
17.
Zurück zum Zitat Zhang, D.-G., Liu, S., Zhang, T., & Liang, Z. (2017). Novel unequal clustering routing protocol considering energy balancing based on network partition & distance for mobile education. Journal of Network and Computer Applications, 88, 1–9.CrossRef Zhang, D.-G., Liu, S., Zhang, T., & Liang, Z. (2017). Novel unequal clustering routing protocol considering energy balancing based on network partition & distance for mobile education. Journal of Network and Computer Applications, 88, 1–9.CrossRef
18.
Zurück zum Zitat Yuan, H.-Y., Yang, S.-Q., & Yi Y.-Q. (2011). An energy-efficient unequal clustering method for wireless sensor networks," in 2011 international conference on computer and management (CAMAN) (pp. 1–4). IEEE. Yuan, H.-Y., Yang, S.-Q., & Yi Y.-Q. (2011). An energy-efficient unequal clustering method for wireless sensor networks," in 2011 international conference on computer and management (CAMAN) (pp. 1–4). IEEE.
19.
Zurück zum Zitat Wang, J., Cao, Y., Cao, J., Ji, H., & Yu, X. (2016). Energy-balanced unequal clustering routing algorithm for wireless sensor networks. In Advances in computer science and ubiquitous computing (pp. 352–359). Springer. Wang, J., Cao, Y., Cao, J., Ji, H., & Yu, X. (2016). Energy-balanced unequal clustering routing algorithm for wireless sensor networks. In Advances in computer science and ubiquitous computing (pp. 352–359). Springer.
20.
Zurück zum Zitat Purkait, R., & Tripathi, S. (2015). Fuzzy based unequal energy aware clustering with multi-hop routing in wireless sensor network. In 2015 IEEE workshop on computational intelligence: theories, applications and future directions (WCI) (pp. 1–10). IEEE. Purkait, R., & Tripathi, S. (2015). Fuzzy based unequal energy aware clustering with multi-hop routing in wireless sensor network. In 2015 IEEE workshop on computational intelligence: theories, applications and future directions (WCI) (pp. 1–10). IEEE.
21.
Zurück zum Zitat Li, H., Liu, Y., Chen, W., Jia, W., Li, B., & Xiong, J. (2013). COCA: Constructing optimal clustering architecture to maximize sensor network lifetime. Computer Communications, 36(3), 256–268.CrossRef Li, H., Liu, Y., Chen, W., Jia, W., Li, B., & Xiong, J. (2013). COCA: Constructing optimal clustering architecture to maximize sensor network lifetime. Computer Communications, 36(3), 256–268.CrossRef
22.
Zurück zum Zitat Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.CrossRef Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.CrossRef
23.
Zurück zum Zitat Kang, S. H., & Nguyen, T. (2012). Distance based thresholds for cluster head selection in wireless sensor networks. IEEE Communications Letters, 16(9), 1396–1399.CrossRef Kang, S. H., & Nguyen, T. (2012). Distance based thresholds for cluster head selection in wireless sensor networks. IEEE Communications Letters, 16(9), 1396–1399.CrossRef
24.
Zurück zum Zitat Chen, C., Rao, F., Zhang, X., & Dong, Y. (2015). An asynchronous cluster head rotation scheme for wireless sensor networks. In 2015 International wireless communications and mobile computing conference (IWCMC) (pp. 551–556). IEEE. Chen, C., Rao, F., Zhang, X., & Dong, Y. (2015). An asynchronous cluster head rotation scheme for wireless sensor networks. In 2015 International wireless communications and mobile computing conference (IWCMC) (pp. 551–556). IEEE.
25.
Zurück zum Zitat Gajendran, E. (2017). Ring structured clustering algorithm in wireless sensor networks using integrated clustering. Asian Journal of Applied Science and Technology (AJAST), 1, 380–390. Gajendran, E. (2017). Ring structured clustering algorithm in wireless sensor networks using integrated clustering. Asian Journal of Applied Science and Technology (AJAST), 1, 380–390.
26.
Zurück zum Zitat Panag, T. S., & Dhillon, J. (2018). Dual head static clustering algorithm for wireless sensor networks. AEU-International Journal of Electronics and Communications, 88, 148–156.CrossRef Panag, T. S., & Dhillon, J. (2018). Dual head static clustering algorithm for wireless sensor networks. AEU-International Journal of Electronics and Communications, 88, 148–156.CrossRef
27.
Zurück zum Zitat Gupta, V., & Pandey, R. (2016). An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks. An International Journal of Engineering Science and Technology 19(2), 1050–1058.CrossRef Gupta, V., & Pandey, R. (2016). An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks. An International Journal of Engineering Science and Technology 19(2), 1050–1058.CrossRef
28.
Zurück zum Zitat Yang, J., & Zhang, D. (2009). An energy-balancing unequal clustering protocol for wireless sensor networks. Information Technology Journal, 8(1), 57–63.CrossRef Yang, J., & Zhang, D. (2009). An energy-balancing unequal clustering protocol for wireless sensor networks. Information Technology Journal, 8(1), 57–63.CrossRef
29.
Zurück zum Zitat Ever, E., Luchmun, R., Mostarda, L., Navarra, A., & Shah, P. (2012). Uheed-an unequal clustering algorithm for wireless sensor networks. Ever, E., Luchmun, R., Mostarda, L., Navarra, A., & Shah, P. (2012). Uheed-an unequal clustering algorithm for wireless sensor networks.
30.
Zurück zum Zitat Han, T., Bozorgi, S. M., Orang, A. V., Hosseinabadi, A. A. R., Sangaiah, A. K., & Chen, M.-Y. (2019). A hybrid unequal clustering based on density with energy conservation in wireless nodes. Sustainability, 11(3), 746.CrossRef Han, T., Bozorgi, S. M., Orang, A. V., Hosseinabadi, A. A. R., Sangaiah, A. K., & Chen, M.-Y. (2019). A hybrid unequal clustering based on density with energy conservation in wireless nodes. Sustainability, 11(3), 746.CrossRef
31.
Zurück zum Zitat Yu, B., Choi, W., Lee, T., & Kim, H. (2018). Clustering algorithm considering sensor node distribution in wireless sensor networks. Journal of Information Processing Systems, 14(4), 926–940. Yu, B., Choi, W., Lee, T., & Kim, H. (2018). Clustering algorithm considering sensor node distribution in wireless sensor networks. Journal of Information Processing Systems, 14(4), 926–940.
32.
Zurück zum Zitat Lai, W. K., Fan, C. S., & Lin, L. Y. (2012). Arranging cluster sizes and transmission ranges for wireless sensor networks. Information Sciences, 183(1), 117–131.CrossRef Lai, W. K., Fan, C. S., & Lin, L. Y. (2012). Arranging cluster sizes and transmission ranges for wireless sensor networks. Information Sciences, 183(1), 117–131.CrossRef
33.
Zurück zum Zitat Lobiyal, D. (2018). Energy consumption reduction in S-MAC protocol for wireless sensor network. Procedia Computer Science, 143, 757–764.CrossRef Lobiyal, D. (2018). Energy consumption reduction in S-MAC protocol for wireless sensor network. Procedia Computer Science, 143, 757–764.CrossRef
34.
Zurück zum Zitat Kritsis, K., Papadopoulos, G. Z., Gallais, A., Chatzimisios, P., & Theoleyre, F. (2018). A tutorial on performance evaluation and validation methodology for low-power and lossy networks. IEEE Communications Surveys and Tutorials, 20(3), 1799–1825.CrossRef Kritsis, K., Papadopoulos, G. Z., Gallais, A., Chatzimisios, P., & Theoleyre, F. (2018). A tutorial on performance evaluation and validation methodology for low-power and lossy networks. IEEE Communications Surveys and Tutorials, 20(3), 1799–1825.CrossRef
35.
Zurück zum Zitat Li, Z., Liu, Y., Liu, A., Wang, S., & Liu, H. (2018). Minimizing convergecast time and energy consumption in green Internet of Things. IEEE transactions on emerging topics in computing, 8, 797–813. Li, Z., Liu, Y., Liu, A., Wang, S., & Liu, H. (2018). Minimizing convergecast time and energy consumption in green Internet of Things. IEEE transactions on emerging topics in computing, 8, 797–813.
36.
Zurück zum Zitat Khan, W. Z., Saad, N., & Aalsalem, M. Y. (2012). An overview of evaluation metrics for routing protocols in wireless sensor networks. In 2012 4th international conference on intelligent and advanced systems (ICIAS2012), 2012 (vol. 2, pp. 588–593). IEEE. Khan, W. Z., Saad, N., & Aalsalem, M. Y. (2012). An overview of evaluation metrics for routing protocols in wireless sensor networks. In 2012 4th international conference on intelligent and advanced systems (ICIAS2012), 2012 (vol. 2, pp. 588–593). IEEE.
37.
Zurück zum Zitat Sha, K., Du, J., & Shi, W. (2006). WEAR: A balanced, fault-tolerant, energy-aware routing protocol in WSNs. International Journal of Sensor Networks, 1(3–4), 156–168.CrossRef Sha, K., Du, J., & Shi, W. (2006). WEAR: A balanced, fault-tolerant, energy-aware routing protocol in WSNs. International Journal of Sensor Networks, 1(3–4), 156–168.CrossRef
Metadaten
Titel
A hybridization strategy using equal and unequal clustering schemes to mitigate idle listening for lifetime maximization of wireless sensor network
verfasst von
Nura Modi Shagari
Mohd Yamani Idna Idris
Rosli Bin Salleh
Ismail Ahmedy
Ghulam Murtaza
Aznul Qalid Bin Md Sabri
Publikationsdatum
05.04.2021
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 4/2021
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-021-02608-z

Weitere Artikel der Ausgabe 4/2021

Wireless Networks 4/2021 Zur Ausgabe

Neuer Inhalt