We derive a new representation for the collusive sensor nodes when the underlying fraudulent correlated environment has strong influence on wireless sensor networks performance. We have evaluated collusion effect with respect to static (SW) and dynamic (DW) wireless sensor networks to derive the joint resultant. Moreover accuracy, path length, and energy consumption of sensor node operations are also evaluated. Additionally, we emphasized over the satisfaction evaluation for linguistic fuzzy trust and reputation (LFTM) models in the deployed WSN framework. Finally, simulation analysis has been carried out to prove the validity of our proposal. However, collusion for wireless sensor networks seems intractable with the static and dynamic WSNs when varied with specified number of fraudulent nodes in the scenario.
Trust and reputation models emerges new facet that aims to provide secure and reliable computations in distributed computational environment. In this manuscript, we propose pervasive explorations of wireless sensor network to investigate the effect of static, dynamic and oscillating modes. Our proposed model constitutes five trust and reputation models namely: bio-inspired trust and reputation, Eigen trust, peer trust, power trust, linguistic fuzzy trust and reputation. The impact of different wireless sensor networks modes has been judged for accuracy, path length and energy consumption over deployed models. Further experimental results have demonstrated to prove the validity of our proposal.
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