Xiao Liu PhD Thesis.pdf - Faculty of Information and Communication ...
Xiao Liu PhD Thesis.pdf - Faculty of Information and Communication ...
Xiao Liu PhD Thesis.pdf - Faculty of Information and Communication ...
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the previous one <strong>and</strong> the service provider re-evaluates the consistency state, until it<br />
reaches or is above the minimum probability threshold.<br />
In contrast, the probability oriented negotiation process begins with the user’s<br />
initial suggestion <strong>of</strong> a probability value <strong>of</strong> α % , the service provider evaluates the<br />
execution time R(SW<br />
) <strong>of</strong> the entire workflow process SW by the sum <strong>of</strong> all activity<br />
n<br />
durations as ∑ w i ( µ i + λσ i ) , where λ is the α % percentile. If R(SW<br />
) is above the<br />
i=<br />
1<br />
maximum upper bound constraint <strong>of</strong> max(SW ) for the user, the probability value<br />
needs to be adjusted, otherwise the negotiation process terminates. The following<br />
process is the iteration that the user proposes a new probability value which is lower<br />
than the previous one <strong>and</strong> the service provider re-evaluates the workflow duration,<br />
until it reaches or is lower than the upper bound constraint.<br />
Figure 5.6 Negotiation Process for Setting Coarse-Grained Temporal<br />
Constraints<br />
As depicted in Figure 5.6, with the probability based temporal consistency, the<br />
time oriented negotiation process is normally where increasing upper bound<br />
constraints are proposed <strong>and</strong> evaluated with their temporal probability consistency<br />
states until the probability is above the user’s bottom-line confidence, while the<br />
probability oriented negotiation process is normally where decreasing temporal<br />
probability consistency states are proposed <strong>and</strong> estimated with their upper bound<br />
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