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

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temporal violations is very small, their temporal violation handling strategies also need to be investigated. Since these heavy-weight strategies are normally very expensive and sophisticated, how to make the best use of these strategies and reduce their cost to the minimal are challenging issues. 170
Bibliography [1] W. M. P. van der Aalst and K. M. V. Hee, Workflow Management: Models, Methods, and Systems: The MIT Press, Cambridge, 2002. [2] W. M. P. van der Aalst, K. M. V. Hee, and H. A. Reijers, "Analysis of Discrete-Time Stochastic Petri Nets", Statistica Neerlandica, vol. 54, no. 1, pp. 237-255, 2000. [3] S. Akioka and Y. Muraoka, "Extended Forecast of CPU and Network Load on Computational Grid", Proc. IEEE International Symposium on Cluster Computing and the Grid (CCGrid2004), pp. 765-772, Chicago, Illinois, USA, Apr. 2004. [4] M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, G. Lee, D. A. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, "Above the Clouds: A Berkeley View of Cloud Computing", Technical Report, University of California at Berkeley, www.eecs.berkeley.edu/Pubs/ TechRpts/2009/EECS-2009-28.pdf, accessed on 1 st Nov. 2010. [5] J. Behnamian, M. Zandieh, and S. M. T. Fatemi Ghomi, "Parallel-Machine Scheduling Problems with Sequence-Dependent Setup Times Using an ACO, SA and VNS Hybrid Algorithm", Expert Systems with Applications, vol. 36, no. 6, pp. 9637-9644, 2009. [6] C. Blum and A. Roli, "Metaheuristics in Combinatorial Optimization: Overview and Conceptual Comparison", ACM Computing Survey, vol. 35, no. 3, pp. 268-308, 2003. [7] G. Boss, P. Malladi, D. Quan, L. Legregni, and H. Hall, "IBM Cloud Computing (White Paper) ", Technical Report, http://download.boulder.ibm. com/ibmdl/pub/software/dw/wes/hipods/Cloud_computing_wp_final_8Oct.p df, accessed on 1 st Nov. 2010. [8] G. Bucci, L. Sassoli, and E. Vicario, "Correctness Verification and Performance Analysis of Real-Time Systems Using Stochastic Preemptive Time Petri Nets", IEEE Trans. on Software Engineering, vol. 31, no. 11, pp. 913-927, 2005. [9] P. A. Buhr and W. Y. R. Mok, "Advanced Exception Handling Mechanisms", 171
Page 1 and 2:
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
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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
Page 151 and 152: value to sample all of the solution
Page 153 and 154: mapping task a i to resource R j fr
Page 155 and 156: have done some simulation experimen
Page 157 and 158: violations can still be recovered b
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
Page 165 and 166: strategy; and End(Rescheduling) is
Page 167 and 168: (a) Optimisation Ratio on Total Cos
Page 169 and 170: makespan. In our two stage workflow
Page 171 and 172: espectively. It is clearly that ACO
Page 173 and 174: comparison results on the violation
Page 175 and 176: percentiles. The average global vio
Page 177 and 178: equivalent times of ACOWR are calcu
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: which can be further investigated i
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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