Sensors Augmentation Influence Over Trust and Reputation Models Realization for Dense Wireless Sensor Networks

Abstract

This paper reports the power consumption and resource utilization of a trust and reputation model deployed in a wireless sensor network. The impact of sensor augmentation parameter for static and dynamic wireless sensor network (WSN) with trust and reputation models has been examined. Specifically, we present a novel WSN framework based investigations on peer trust and Linguistic Fuzzy Trust Model (LFTM) for trust and reputation models. Accuracy, path length and energy consumption of sensor node operations are reported for their current and average scenarios. Additionally, we emphasized over the satisfaction evaluation for LFTM model in the deployed WSN framework. The performance of the sensor augmentation for our proposed framework is evaluated via analytic bounds and numerical simulations. Analytical results together with simulation results exhibit the eminence of the proposed sensor augmentation based realization over past trust and reputation model investigations.

Autonomic management of group communication for Internet of Things applications

“…In the second scenario, we deployed 20 CoAP nodes in an area of 100 m 2 , denoted as . These network densities are within the set of densities tested by Singh et al 31 and are denser than the network evaluated by Dao et al 3 The event occurrence follows a Poisson distribution with , where each event has a fixed duration of 5 min. In addition, the solutions have been tested in three different SR levels with the aim to observe their performance to disseminate low, mid, and highly relevant data.…”

Multiuser-scheduling and resource allocation using max-min technique in wireless powered communication networks

“…Finally, they provided an indepth analysis in maximizing the secrecy performance by examining optimization problems such as optimal jammer selection under identical transmit power and optimal allocation of power in every transmitter with limited transmit power. Singh et al [24] assessed a WSN framework that uses trust and reputation models to quantify and compare performance across multiple WSN modes, such as static, dynamic, and oscillatory.…”

Pheromone and Path Length Factor-Based Trustworthiness Estimations in Heterogeneous Wireless Sensor Networks

“…A new trust and reputation model by adding additional constraints to BTRM-WSN adopting an interactive multiple ant colony algorithm was also suggested in reference [27]. We enhanced the research work reported in references [27][28][29][30] by incorporating rigorous performance parameters on a composite platform for heterogeneous WSNs. Qureshi et al [28] reported an extension of TRM based on interaction and validation along with collusion issue.…”