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The algorithm provides three outputs: (i) root: the policy at the root of the new policy tree which can reference remote policies, (ii) S P : the set of referenced policies to be deployed provider-side and (iii) S T : the set of referenced policies to be deployed tenant-side.
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Remote policy decision point.
Afterward, the algorithm tries to combine multiple remote policy references into a single reference again, in order to minimize the number of remote policy evaluation requests.
The policy tree resulting from normalizing and decomposing the policies from the case study does not allow to combine multiple remote policy references.
First, remote policy references can be extended with local targets in order to avoid the unnecessary policy requests mentioned in Section 6.3.
Non-sensitive attributes are made available to the other party by means of an attribute service, the PDPs by means of a Remote Policy Decision Point (RPDP).
In case of FirstApplicable, only consecutive remote policy references in the sub-policies can be combined; in case of PermitOverrides or DenyOverrides, all remote policy references can be combined since these algorithms are commutative as shown by transformations T8 and T9 of Equations (T8 T9).
More precisely, the algorithm combines multiple policies referenced in a single composed policy into a larger equivalent composed policy and combines their remote policy references into a reference to the new combined policy.
Finally, the third step of the algorithm tries to combine remote policy references in order to minimize the number of policy evaluation requests between tenant and provider (see Algorithm 4).
This not only leads to a performance overhead because of the additional (possibly remote) policy evaluation, but in data-driven applications such as medical image processsing, this can lead to sending back and forth large data sets between different cloud offerings.
Remote access policies and profiles help accomplish the goal by limiting who is authorized to connect and by limiting how they connect and for how long.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com