Abstract
With the rapid development of sensor technology and wireless network technology, wireless sensor network (WSN) has been widely applied in many resource-constrained environments and application scenarios. As there are a large number of sensor nodes in WSN, node failures are inevitable and have a significant impact on task execution. In this paper, considering the vulnerability, unreliability, and dynamic characteristics of sensor nodes, node failures are classified into two categories including unrecoverable failures and recoverable failures. Then, the traditional description of the interaction results is extended to the trinomial distribution. According to the Bayesian cognitive model, the global trust degree is aggregated by both direct and indirect interaction records, and a novel trust model based on node recovery technique for WSNs is proposed to reduce the probability of failure for task execution. Simulation results show that compared with existing trust models, our proposed TMBNRT (trust model based on node recovery technique) algorithm can effectively meet the security and the reliability requirements of WSN.
Highlights
Wireless sensor network (WSN) often consists of thousands of spatially dispersed and dedicated sensors which are smallsized and resource-constrained [1]
Some progress has been achieved in this area, obvious limitations still remain as the classification of node failures is not detailed enough. e traditional trust model describes the interaction results between two sensor nodes by binomial events
From the security and reliability points of view, we propose and implement a novel trust model based on the node recovery technique in WSN by extending the traditional binomial description to the trinomial distribution for the interaction results which is more accurate for describing the interaction results between different sensor nodes
Summary
Wireless sensor network (WSN) often consists of thousands of spatially dispersed and dedicated sensors which are smallsized and resource-constrained [1]. LTMBE algorithm uses direct trust value alone when the confidence coefficient is above the certain threshold in order to meet the resource limitations of tiny sensor nodes in WSNs. some progress has been achieved in this area, obvious limitations still remain as the classification of node failures is not detailed enough. E traditional trust model describes the interaction results between two sensor nodes by binomial events (successful interaction and failure interaction). From the security and reliability points of view, we propose and implement a novel trust model based on the node recovery technique in WSN by extending the traditional binomial description to the trinomial distribution for the interaction results (viz., successful interaction, unrecoverable failures, and recoverable failures) which is more accurate for describing the interaction results between different sensor nodes.
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