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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expected time redundancy <strong>of</strong> subsequent activities, i.e. self-recovery. For a<br />
necessary <strong>and</strong> sufficient checkpoint where a temporal violation is detected, the<br />
occurred time deficit <strong>and</strong> the expected time redundancy <strong>of</strong> subsequent activities after<br />
the checkpoint are the basic factors used to decide whether a checkpoint should be<br />
selected as a temporal violation h<strong>and</strong>ling point or not. Therefore, an effective<br />
strategy is required to estimate the probability <strong>of</strong> self-recovery so as to facilitate<br />
temporal violation h<strong>and</strong>ling point selection in scientific workflow systems.<br />
7.2 Adaptive Temporal Violation H<strong>and</strong>ling Point Selection Strategy<br />
7.2.1 Probability <strong>of</strong> Self-Recovery<br />
The details <strong>of</strong> the probability based temporal consistency model are presented in<br />
Section 5.2 <strong>and</strong> hence omitted here. Given the probability based temporal<br />
consistency model, we can quantitatively measure different temporal violations<br />
based on their probability temporal consistency states. Furthermore, at a specific<br />
checkpoint, the occurred time deficit <strong>and</strong> the expected time redundancy <strong>of</strong><br />
subsequent activities need to be estimated. They are defined as follows.<br />
Definition 7.1: (Probability Time Deficit).<br />
At activity point<br />
a p , let U (SW ) be <strong>of</strong> β % C with the percentile <strong>of</strong> λ β which is<br />
below the threshold <strong>of</strong> θ % with the percentile <strong>of</strong> λ θ . Then the probability time<br />
deficit <strong>of</strong> U (SW ) at a p is defined as<br />
PTD U(<br />
SW),<br />
a ) = [ R(<br />
a1,<br />
a ) + θ ( a + 1,<br />
a )] −u(<br />
SW)<br />
. Here,<br />
( p<br />
n<br />
k<br />
k = p+<br />
1<br />
θ(<br />
a + 1,<br />
) = ∑ ( µ + λθ σ ) .<br />
p a n<br />
k<br />
p<br />
Definition 7.2: (Probability Time Redundancy for Single Workflow Segment).<br />
At activity point<br />
p<br />
a p , let U (SW ) be <strong>of</strong> β % C with the percentile <strong>of</strong> λ β which is<br />
above the threshold <strong>of</strong> θ % with the percentile <strong>of</strong> λ θ . The subsequent activities are<br />
defined as those activities from the next activity <strong>of</strong> the checkpoint, i.e. a p+ 1, to the<br />
n<br />
end activity <strong>of</strong> the next temporal constraint, e.g.<br />
a p + m . With a segment <strong>of</strong> size m<br />
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