Open AccessEfficient aggregation technique for data privacy in wireless sensor networks
Author(s) -
Raja Manjula,
Datta Raja
Publication year - 2018
Publication title -
iet networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 21
ISSN - 2047-4962
DOI - 10.1049/iet-net.2017.0104
Subject(s) - data aggregator , computer science , overhead (engineering) , wireless sensor network , reliability (semiconductor) , computer network , aggregate (composite) , base station , node (physics) , distributed computing , data transmission , modular design , cluster analysis , wireless , chinese remainder theorem , constraint (computer aided design) , transmission (telecommunications) , communication complexity , private information retrieval , theoretical computer science , algorithm , engineering , computer security , telecommunications , mechanical engineering , power (physics) , physics , materials science , structural engineering , quantum mechanics , machine learning , composite material , operating system
In wireless sensor networks (WSNs), the existing cluster‐based private data aggregation techniques are energy‐intensive due to high message transmission complexity. Reliable data transmissions are also vital for resource constraint WSNs. To address these issues, the authors propose a reliability enabled private data aggregation technique that has message transmission complexity of O ( N ) . Every node in the cluster cleaves its data into n integrants using simple modular arithmetic with suitable prime moduli and transmits to the cluster heads (CHs) for intermediate aggregation. The CHs, in turn, forward the partial aggregate data to the base station where the final aggregate is recovered using an elegant Chinese remainder theorem. The authors use data privacy, communication overhead, and reliability metrics to gauge the performance of the proposed work. Numerical and simulation results demonstrate that the proposed solution outperforms the existing schemes having O ( N 2 ) communication complexity.