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Finally, the updated trust value is used for global trust evaluation.
CHs report the updated trust value of cognitive users in its related sub-network to FC in period Treport.
There are two update forms of trust value stored in FC: CHs report the updated trust value of cognitive users in its related sub-network to FC in period Treport.
The updated trust value is calculated using the previous trust value and impact of current interaction in the form of reward/penalty rate using following equation: T i = T i - 1 + Δ p for I cur = positive interaction T i - 1 - Δ n for I cur = negative interaction.
Similar(56)
Unlike in [12] where a mesh-like approach used to calculate trust by each node in the network has needs to update trust table of all nodes in the network and resources are wasted on updating trust values if node may expire before being used.
Function lub_trustty has a straightforward definition and update_trusty receives as parameters a type (tau =t^{s}) and a trust annotation (s') and updates the trust annotation on type (tau ) to (svee s').
Interaction relates to the trust value evaluation among cognitive users in the communication process to update the trust value.
The buyer agent will then update its trust on its seller agents once it finishes a transaction or receives a reference trust from other buyer agents.
Nodes in the network monitor the behavior of each other and continuously update their trust tables.
Approach 2 FC conducts polling to all the cognitive users inside the network periodically and update the trust value matrix.
For updating the trust value of a node, the following function is used as shown in (1): 1 - T new = a 1 - T old + b 1 - T c - F (1). where a and b represent the weightage corresponding to the old trust and new trust values of the node.
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