One usually starts with the single KOs and KIs: one clamps the logical value (0 or 1, respectively) of the respective node, computes the resulting logical steady state (as explained above) and verifies whether the intervention goal is achieved.
Each node in this layer is connected to the respective node in layer 3, and also the initial inputs x and (y).
In such a case, the respective node of the search tree has (n) child nodes.
The columns with the hash character reflect the ranking for the respective node selection.
Such corresponds to the difference of the within-node variance between a respective node and the two resulting sub-nodes.
After receiving CH_RELEIVE, all the nodes calculate the respective node values and convey them to the CH.
For example: a detected attack could be mitigated by rejuvenating components more frequently; a detected intrusion could be amended by immediately rejuvenating the respective node.
Therefore, each node of a tree is represented trough a case weights vector (varvec{w} = left( {w_{1}, ldots,w_{n} } right)) ((n =) total number of observations) with (w_{i} ne 0) if the respective node contains the corresponding observation, else (w_{i} = 0).
Since a new traffic assignment problem is solved for each iteration and hence a new set of the shortest paths are calculated, the algorithm implicitly considers the betweenness (note that the betweenness refers to a total number of shortest paths passing through a respective node).
This is achieved by replacing each of the nodes that correspond to variables C L j k in G c with the appropriate G j, using j as selection criterion and maintaining that the parent node of G j takes the position of the respective node in G c. Thus, the resulting overall BN structure, denoted by G, comprises of a set of sub-structures integrated to the DAG depicted in Figure 3b.
They displayed that two removal schemes flow-based and betweenness-based inflict the highest disruption compared to other removal scenarios (betweenness is an indicator of a node's centrality in a network, and it is equal to the number of shortest paths that pass through the respective node).
