Reference pattern-based data aggregation in a wireless sensor network
DOI:
https://doi.org/10.47264/idea.ajset/4.2.1Keywords:
Pattern code, Reference value, Cluster, Computing hardware, Energy consumption, Simulation results, Energy conservation, Data transmission, Sensed dataAbstract
Data aggregation is a proven technique for mitigating issues in wireless sensor networks. In this paper, reference pattern-based data aggregation in a wireless sensor network is utilised for data aggregation to conserve energy and eliminate redundancy in a wireless sensor network. In traditional data aggregation, each node forwards its data to the cluster head, which aggregates it and then forwards it to the base station. This process takes higher energy. However, in energy-efficient secure pattern-based data aggregation (ESPDA), each sensor node initially generates a pattern code from a lookup table based on the sensed data and then transmits the data to the cluster head. Pattern codes are indicative of sensed data and compact in size. Production of pattern codes from a lookup table is problematic. First, creating a lookup table consumes more computational resources; second, searching for critical values within the corresponding interval also consumes more computational resources and energy. In this research, a new mechanism has been proposed to reduce the consumption of computational and energy resources. We used a reference-based mechanism to create the pattern codes. The simulation results indicate that the proposed mechanism is more energy and computation-efficient than ESPDA.
References
Chan, H., Perrig, A., & Song, D. (2006, October). Secure hierarchical in-network aggregation in sensor networks. In Proceedings of the 13th ACM conference on Computer and Communications Security (pp. 278–287). https://doi.org/10.1145/1180405.1180440
Çam, H., Özdemir, S., Nair, P., Muthuavinashiappan, D., & Sanli, H. O. (2006). Energy-efficient secure pattern-based data aggregation for wireless sensor networks. Computer Communications, 29(4), 446–455. https://doi.org/10.1016/j.comcom.2004.12.029
Heinzelman, W. B. (2000). Application-specific protocol architectures for wireless networks. Doctoral dissertation, Massachusetts Institute of Technology. https://dspace.mit.edu/handle/1721.1/26881
Hu, L. & Evans, D. (2003). Secure data aggregation for wireless network. In Symposium on Applications and the Internet (SAINT) Workshops, IEEE Computer Society (pp. 384–394).
Khedhiri, K., Ben Omrane, I., Djabour, D., & Cherif, A. (2025, May). Clustering for Lifetime Enhancement in Wireless Sensor Networks. Telecom, 6(2), 30. https://doi.org/10.3390/telecom6020030
Murthy, C. S. R., & Manoj, B. S. (2004). Ad hoc wireless networks: Architectures and protocols. Pearson Education.
Ozdemir, S., & Xiao, Y. (2009). Secure data aggregation in wireless sensor networks: A comprehensive overview. Computer Networks, 53(12), 2022-2037. https://doi.org/10.1016/j.comnet.2009.02.023
OzgurSanli, H., Ozdemir, S., & Cam, H. (2004, September). SRDA: Secure Reference-Based Data Aggregation Protocol for Wireless Sensor Networks, in IEEE 60th Conference on Vehicular Technology, VTC 2004-Fall, Volume 7, pp. 4650–4654, 26–29.
Reddy, M. R, Ravi Chandra, M. L., Venkatramana, P., & Dilli, R. (2023). Energy-efficient cluster head selection in wireless sensor networks using an improved grey wolf optimisation algorithm. Computers, 12(2), 35. https://doi.org/10.3390/computers12020035
Saadallah, N. R., & Alabady, S. A. (2024). An energy-efficient and scalable WSN with enhanced data aggregation accuracy. Journal of Telecommunications and Information Technology, (2), 48–57. https://doi.org/10.26636/jtit.2024.2.1510
Sharmin, S., Ahmedy, I., & Md Noor, R. (2023). An energy-efficient data aggregation clustering algorithm for wireless sensor Networks using hybrid PSO. Energies, 16(5), 2487. https://doi.org/10.3390/en16052487
Yuan, H., & Gao, C. (2025). Minimising redundancy in wireless sensor networks using sparse vectors. Sensors, 25(5), 1557. https://doi.org/10.3390/s25051557
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Tahir Saleem, Khadija Sarwar, Umar Ayaz Khan, Muhammad Shaheer, Hannan Adeel, Inam ur Rehman Rao
This work is licensed under a Creative Commons Attribution 4.0 International License.
Please click here for details about AJSET's Licensing and Copyright policies.
