The performance calculation of Web services composition process in large state space is time-consuming
and is difficult to fulfill the real-time performance analysis.Therefore
a process reduction algorithm is presented to accelerate the calculation of system performance. The Web services composition process is modeled using the generalized stochastic Petri net. Through auto-detecting the reductive subnet
some regular structures
such as sequence
choice
concurrent and loop structures
can be eliminated under the precondition of preserving the timing constraints. The sub processes which can be calculated independently are separated. A large scale model can thus be reduced within a certain period. Experimental results with multiform models indicate that the system response time and throughput are obtained rapidly by using the algorithm in the dynamic and adaptive composition process. The algorithm can be applied to online performance analysis of most Web services composition process.
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