In wireless sensor networks, the characteristics of the openness and vulnerability can lead to communication failure and node capture more easily. To cope with the deviation problem caused by the compromised nodes, this paper proposes a situation data fusion mechanism which can enhance reliability and integrality. It makes a reliability assurance scheme, which not only establishes a project distinguishing purposive and purposeless acts, but also builds a trust awareness rule based on historical trust and the correlations among current nodes. Furthermore, the data integrality is ensured in three stages, respectively. Firstly, in event detection stage, the proposed mechanism detects events and pretreats data to improve accuracy through most trust majority rule after collecting data. Moreover, during data fusion stage, data filtration is adopted to extract credible data. Additionally, the fusion weights of transactions depend on trust, so that they will change with the passage of time. As a result, the final fusion data will be closer to real value. Finally, in consistency detection stage, the detection rule with lower communication traffic is utilized to judge whether the centers are credible. Theory analyses and simulation results verify that the new mechanism can reduce the deviation. Meanwhile, reliability and stability have been validly enhanced.
Li et al. REF proposed a fusion mechanism MCMR based on trust, which considered historical and time correlation and draws up situation trust awareness rule on historical trust and current data correlation.
Event-Centric Situation Trust Data Aggregation Mechanism in Distributed Wireless Network
International Journal of Distributed Sensor Networks
Computer Science