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

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An innovative setting strategy has been presented in this thesis. The coarsegrained temporal constraints are assigned through an either time-oriented or probability-oriented negotiation process between service users and service providers. Afterwards, based on those coarse-grained temporal constraints, fine-grained temporal constraints can be propagated along scientific cloud workflows in an automatic fashion. 5) A novel strategy for temporal violation handling point selection Conventional temporal verification work conducts temporal violation handling on every selected necessary and sufficient checkpoint. However, based on the analysis in this thesis, we have identified the phenomenon of self-recovery where minor temporal violations can usually be auto-recovered by the reduced execution time of the subsequent workflow activities. Therefore, a novel adaptive temporal violation handling point selection strategy has been proposed to further select a subset of the checkpoints as temporal violation handling points for handling temporal violations. The experimental results have shown that our strategy can significantly reduce the times of temporal violation handling while maintain satisfactory temporal correctness. 6) An innovative general metaheuristics based workflow rescheduling strategy This thesis focuses on light-weight temporal violation handling strategies for recoverable temporal violations. Specifically, we have designed a general two-stage workflow local rescheduling strategy which utilises metaheuristics algorithms to optimise the integrated Task-Resource list. The general strategy has been further implemented with GA and ACO. The experimental results have shown that it can effectively compensate time deficits without recruiting additional resources. 9.4 Future Work This thesis has proposed a novel probabilistic framework to realise a lifecycle support of temporal QoS in scientific cloud workflow systems. The future work will focus on how to improve the overall performance of the framework and further reduce the cost of temporal violation handling. Specifically, there are six aspects 168
which can be further investigated in the future: 1) Forecasting strategy: our forecasting strategy focuses on data/computation intensive activities. In the future, we will investigate the adaptation of our forecasting strategy for other types of cloud workflow activities such as instance intensive activities in business cloud workflow applications. 2) Setting strategy: our setting strategy can achieve a set of high quality coarsegrained and fine-grained temporal constraints at build time. In the future, we will investigate the updating strategy for temporal constraints at runtime to accommodate significant changes such as new user requirements and QoS contract changes. 3) Checkpoint selection and temporal verification: with the novel probability based temporal consistency model, our strategy can significantly reduce the times for checkpoint selection and temporal verification. In the future, the time-series patterns for different types of temporal violations will be investigated to further improve the efficiency of checkpoint selection and temporal verification. 4) Temporal violation handling point selection: the experimental results have shown that our adaptive temporal violation handling strategy can achieve satisfactory performance in most simulated system environments. In the future, we will test our strategy with more real world workflow applications. 5) Light-weight temporal violation handling strategies: more metaheuristics algorithms will be investigated and compared with our general two-stage workflow local rescheduling strategy. Meanwhile, some other light-weight strategies may also be investigated to supplement standalone rescheduling strategies, especially to overcome the scenarios when the work loads of current resources are very high. 6) Non-recoverable temporal violations: This thesis has focused on statistically recoverable temporal violations. Although the probability of non-recoverable 169
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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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work and problem analysis. Section
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expected time redundancy of subsequ
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the probability for self-recovery i
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skipped if self-recovery applies. A
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To evaluate the average performance
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activities and around 300 violation
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
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Page 149 and 150: For example, in Figure 8.2, local w
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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 179 and 180: Chapter 9 Conclusions and Future Wo
Page 181 and 182: the real world, simulation experime
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Page 185: the whole lifecycle support for hig
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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