Xiao Liu PhD Thesis.pdf - Faculty of Information and Communication ...

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(a) Local Violation Rate (b) Global Violation Rate Figure 8.12 Handling of Temporal Violations Figure 8.12(b) shows the results on global violation rates. Since PTDA has no effect on global violations, the global violation rates for NIL and PTDA are overlapping. The global violation rates for NIL and PTDA behave very unstably but increase roughly with the number of activities while decreasing with the value of normal 156
percentiles. The average global violation rates for NIL and PTDA in each round are 14.6%, 13.8% and 9.0% respectively. With our temporal framework, the global violation rate is kept close to zero since most local temporal violations are handled automatically along workflow executions. The average global violation rates of our temporal framework in each round are 0.2%, 0.0% and 0.3% respectively, i.e. an overall average of 0.167%. In our three-level temporal violation handling strategy, PTDA is only responsible for level I violations and it is applied together with ACOWR for larger violations. Standalone ACOWR handles level II violations and its capability is defined according to its average CompensationRatio which is 58.5% given the experimental results shown in Figure 8.10. As for PTDA+ACOWR (where the maximum iteration times for ACOWR are set as 2), since the initial temporal consistency is around 90% and the average local violation rate for the three rounds of experiments are 0.13% (which is very close to 0%), the average CompensationRatio for PTDA+ACOWR should be around or over 90% so as to maintain such a near 0% local violation rate. 8.6.2 Cost Analysis for Three-Level Handling Strategy We first take a look at the number of temporal violations (including all the three levels of temporal violations, and non-recoverable temporal violation if any) in scientific workflows. Since our checkpoint selection strategy is of necessary and sufficient, the results on the number of temporal violations are exactly the same as the number of checkpoints in scientific workflows as shown in Figure 6.2. The results have shown that the number of temporal violations increases accordingly with the growth of workflow size and the noises. Here, for the ease of discussion without losing generality, we conduct the cost analysis based on the results on temporal violations for COM(1.28) without noises. In our temporal framework, there are three temporal violation handling strategies including PTDA, ACOWR and PTDA+ACOWR. As can be seen in Figure 8.6, the computation cost of PTDA is negligible compared with that of ACOWR. In such a case, the cost of PTDA+ACOWR (including a maximum 2 times for ACOWR) can be regarded either the same or twice as that of ACOWR depending on how many times that ACOWR is facilitated. Therefore, to ease our discussion, we can use the 157
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A Novel Probabilistic Temporal Fram
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Declaration This thesis contains no
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Abstract Cloud computing is a lates
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Component 2, the state of scientifi
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http://dx.doi.org/10.1016/j.jpdc.20
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17. X. Liu, J. Chen, and Y. Yang, A
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4.2 RELATED WORK AND PROBLEM ANALYS
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STRATEGY ..........................
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FIGURE 7.4 EXPERIMENTAL RESULTS (NO
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Chapter 1 Introduction This thesis
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Clearly, if the execution time of t
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to seek all the candidates. Further
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e unnecessary. Hence, an effective
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temporal violations, viz. recoverab
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In Chapter 2, we introduce the rela
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a two-stage searching process with
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QoS requirements. Generally speakin
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handling strategies employed in a s
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activity points to conduct temporal
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compensation, is believed as a suit
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successful completion. Specifically
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Chapter 4 and Chapter 5 respectivel
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etween time deficit compensation an
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service user’s requirements and t
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conducted for three times, i.e. sta
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PTDA+ACOWR as an example to introdu
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currently running. It is built on t
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workflow instance to determine whet
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framework for cost-effective delive
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pattern based forecasting strategy.
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4.2 Related Work and Problem Analys
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4.2.2 Problem Analysis In cloud wor
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significantly deteriorate the overa
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activity durations: characteristics
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specified with different means and
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Table 4.1 Notations Used in K-MaxSD
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1) Duration series building As ment
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Table 4.5 Algorithm 4: Pattern Matc
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to search for those activities whic
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cycle. Here, we also trace back the
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ecognition. Sliding Window ranks in
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predicted value will be the one pre
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segmentation algorithm is capable o
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distributed soft real-time system,
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Table 5.1 Overview on the Support o
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2 2 can be denoted as N ( µ , σ )
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mean iteration times or with some p
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Figure 5.4 Choice Building Block No
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activities may be omitted for the e
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5.3.1 Calculating Weighted Joint Di
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constraints until the constraint is
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Therefore, it can be expressed as n
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Table 5.3 Specification of the Work
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and the constraint for activity X 1
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ease of discussion and to avoid the
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Unfortunately, conventional discret
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The probability consistency range w
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6.2.3 Temporal Checkpoint Selection
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100 times each. All the activity du
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normal distribution and correlated
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Figure 6.3 Checkpoint Selection wit
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Page 127 and 128: the probability for self-recovery i
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Page 131 and 132: To evaluate the average performance
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Page 135 and 136: Figure 7.3 Experimental Results (No
Page 137 and 138: Figure 7.5 Cost Reduction Rate vs.
Page 139 and 140: 8.1 Related Work and Problem Analys
Page 141 and 142: scientific processes, human interve
Page 143 and 144: alone does not involve any time def
Page 145 and 146: swap slower machines in the active
Page 147 and 148: TD( a p ) L{ ( ai , R j ) | i = p +
Page 149 and 150: For example, in Figure 8.2, local w
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Page 153 and 154: mapping task a i to resource R j fr
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Page 159 and 160: PTDA+ACOWR for Level III Violations
Page 161 and 162: an integer from 1 to 5 where the ex
Page 163 and 164: D: Definition for Fitness Value Fit
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Page 167 and 168: (a) Optimisation Ratio on Total Cos
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Page 171 and 172: espectively. It is clearly that ACO
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Page 179 and 180: Chapter 9 Conclusions and Future Wo
Page 181 and 182: the real world, simulation experime
Page 183 and 184: ased temporal consistency model. Ac
Page 185 and 186: the whole lifecycle support for hig
Page 187 and 188: which can be further investigated i
Page 189 and 190: Bibliography [1] W. M. P. van der A
Page 191 and 192: Systems", ACM Trans. on Software En
Page 193 and 194: conjunction with 23 rd Parallel and
Page 195 and 196: Elsevier, vol. 84, no. 3, pp. 354-3
Page 197 and 198: Distributed Computing Systems", Jou
Page 199 and 200: Appendix: Notation Index Symbols α
Page 201 and 202: PTR ( U ( SW ), ( a p + , a p + 1 m
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