Approximate performance analysis of computing process by aggregated HSPN with fuzzy parameters

Abstract

One of the most widespread modern formalisms, used for the model-based performance and dependability evaluation of complex computing systems and networks, with discrete-continuous processes, are the fluid stochastic Petri nets (FSPN) [1] and the hybrid stochastic Petri nets (HSPN) [2] in which one or more finite places (buffers) can hold fluid rather than discrete tokens. However, an FSPN or HSPN model with 3 N buffers cannot be exactly analyzed analytically [1, 2], thus justifying the development of approximation methods.