Homogeneous Clustering Techniques in Wireless Sensor Networks- A Survey

Authors

  • Zainab Rustum Mohsin Department of Computer Science, College of Pure Science, University of Thi-Qar , Thi-Qar, Iraq.

Keywords:

transceivers, , base station, network lifetime, intercluster, latency

Abstract

         Wireless Sensor Network (WSN) is a network made out of huge number of minimal effort, low power and multifunctional sensor hubs that are sent over an unattended zone either near or inside the objectives to be noticed. These sensor hubs are little in size, however are outfitted with sensors, implanted chip and radio handsets and in this manner have detecting ability, yet additionally information handling and imparting capacities. Every single sensor hubs in the organization intermittently sense the states of the objective, measure the information lastly send the detected information back to a Base Station (BS) or sink either in single bounce or in multichip correspondence. On the off chance that immediate correspondence is utilized, hubs which are distant from the sink need more transmission ability to communicate their detected information to sink hub and consequently they drain their energy quicker when contrasted with hubs closer to the sink. In multi bounce correspondence, energy opening shows up close to the sink hub in light of the fact that the hubs closer to the sink hub will convey hefty traffic when contrasted with different hubs. Consequently, no more information can be conveyed to the sink after an energy opening shows up. Thus, a lot of energy is squandered and the organization lifetime closes rashly. To defeat the energy opening issue, homogeneous group based WSN engineering are utilized. The essential thought is to gather hubs around a Cluster Head (CH) that is dependable inter cluster availability. This paper gives an outline of different grouping procedures utilized in WSN in order to keep up network adaptability, load adjusting, and inertness decrease

References

References

Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer communications, 30(14-15), 2826-2841.

Abolfazli, Z., & Mahdavi, M. (2014). A homogeneous wireless sensor network routing algorithm: An energy aware cluster based approach. Paper presented at the 2014 22nd Iranian Conference on Electrical Engineering (ICEE).

Aderohunmu, F. A., Deng, J. D., & Purvis, M. (2011). Enhancing clustering in wireless sensor networks with energy heterogeneity. International Journal of Business Data Communications and Networking (IJBDCN), 7(4), 18-31.

Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). A survey on sensor networks. IEEE Communications magazine, 40(8), 102-114.

Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: a survey. IEEE wireless communications, 11(6), 6-28.

Anisi, M. H., Abdullah, A. H., Coulibaly, Y., & Razak, S. A. (2013). EDR: efficient data routing in wireless sensor networks. International Journal of Ad Hoc and Ubiquitous Computing, 12(1), 46-55.

Chen, Y.-L., & Lin, J.-S. (2012). Energy efficiency analysis of a chain-based scheme via intra-grid for wireless sensor networks. Computer communications, 35(4), 507-516.

Garcia-Marcinkiewicz, A. G., Kovatsis, P. G., Hunyady, A. I., Olomu, P. N., Zhang, B., Sathyamoorthy, M., . . . Franz, A. M. (2020). First-attempt success rate of video laryngoscopy in small infants (VISI): a multicentre, randomised controlled trial. The Lancet, 396(10266), 1905-1913.

Harari, Y. N. (2018). 21 Lessons for the 21st Century: Random House.

Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. Paper presented at the Proceedings of the 33rd annual Hawaii international conference on system sciences.

Kandris, D., Tsagkaropoulos, M., Politis, I., Tzes, A., & Kotsopoulos, S. (2009). A hybrid scheme for video transmission over wireless multimedia sensor networks. Paper presented at the 2009 17th Mediterranean Conference on Control and Automation.

Khediri, S. E., Nasri, N., Wei, A., & Kachouri, A. (2014). A new approach for clustering in wireless sensors networks based on LEACH. Procedia Computer Science, 32, 1180-1185.

Lindsey, S., & Raghavendra, C. S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. Paper presented at the Proceedings, IEEE aerospace conference.

Manjeshwar, A., & Agrawal, D. P. (2001). TEEN: ARouting Protocol for Enhanced Efficiency in Wireless Sensor Networks. Paper presented at the ipdps.

Manjeshwar, A., & Agrawal, D. P. (2002). APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. Paper presented at the Parallel and distributed processing symposium, international.

Muruganathan, S. D., Ma, D. C., Bhasin, R. I., & Fapojuwo, A. O. (2005). A centralized energy-efficient routing protocol for wireless sensor networks. IEEE Communications magazine, 43(3), S8-13.

Pouyan, A. A., Basu, S., Alimohammadi, M., & Hosseinirad, S. M. (2014). LEACH routing algorithm optimization through imperialist approach. International Journal of Engineering, 27(1), 39-50.

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(2), 623-645.

Downloads

Published

2022-04-07