A resilient data aggregation method based on spatio-temporal correlation for wireless sensor networks
TLDR
A resilient data aggregation method based on spatio-temporal correlation for wireless sensor networks that can improve the restoration convergence precision as the attack increment is small and enhance the robustness from noise interference is presented.Abstract:
In wireless sensor networks, the existing data aggregation algorithms usually cannot evaluate the extent of data damage in presence of additive attacks. To resolve such problem, a resilient data aggregation method based on spatio-temporal correlation for wireless sensor networks is presented in this paper. On the basis of the distributed data convergence model, the algorithm combines the centroid distance and similarity to measure the attack degree of each cluster node’s perceived data, and the weighted calculation can improve the convergence precision of data recovery. In addition, this method can obtain the estimated value of data sample of all clusters according to the temporal correlation characteristic of the nodes’ perceived data at different time. Using the chi-square fitting, the extent of the data being tampered in each cluster can be measured effectively. Theoretical analysis and simulation results show our method can improve the restoration convergence precision as the attack increment is small. Also, it can enhance the robustness from noise interference.read more
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References
More filters
Proceedings ArticleDOI
Energy-efficient communication protocol for wireless microsensor networks
TL;DR: The Low-Energy Adaptive Clustering Hierarchy (LEACH) as mentioned in this paper is a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network.
Energy-efficient communication protocols for wireless microsensor networks
TL;DR: LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network, is proposed.
Journal ArticleDOI
Spatio-temporal correlation: theory and applications for wireless sensor networks
TL;DR: A theoretical framework is developed to model the spatial and temporal correlations in WSN to enable the development of efficient communication protocols which exploit these advantageous intrinsic features of the WSN paradigm.
Proceedings ArticleDOI
Resilient aggregation in sensor networks
TL;DR: This paper examines several approaches for making these aggregation schemes more resilient against certain attacks, and proposes a mathematical framework for formally evaluating their security.
Journal ArticleDOI
A novel evolutionary approach for load balanced clustering problem for wireless sensor networks
TL;DR: The proposed GA based load balanced clustering algorithm for WSN is shown to perform well for both equal as well as unequal load of the sensor nodes and the rate of convergence.