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Improving of prediction taking into account the hierarchy of the network
It is necessary for PI to take into account the hierarchy of the network in order to provide more accurate information about relationships between metrics.
Currently, PI prediction is based only on mathematical model and doesn't use topological relationships which cause that PI gives some metrics as related to each other, which can't be related, as they are from different Cells, that have different parent BSCs, from different cities, different domains or even technologies...
Some of the suggested method of supplying relationship information could be: 1. Manual entry of rules to force a relation to form or to NOT form and thus avoid linking metrics from a variety of resources that are not related to each other. 2.Manually add rules that will calculate the distance between entities by having information about entity's position and thus prevent the linking of metrics that originate from entities that are very distant and not related. 3.Import a network topology and then only allow causal relationships between items that have the same parent, grand parent, grand grand parent etc.
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