Compositional specification of real time embedded systems by priority time Petri Nets

Abstract

An important key challenge in Embedded Real Time Systems (ERTS) analysis is to provide a seamless scheduling strategy. Formal methods for checking the temporal characteristics and timing constraints at a high abstraction level have proven to be useful for making the development process reliable. In this paper, we present a Petri Net modeling formalism and an analysis technique which supports not only systems scheduling analysis but also the compositional specification of real time systems. The proposed Priority Time Petri Net gives determinism aspect to the model and accelerates its execution. Indeed, a compositional specification of a PTPN for complex application and multiprocessor architecture that solves the problem of hierarchy is presented.

Transformation process of RTS scheduling analysis requirements from UML/MARTE to dynamic priority time Petri Nets

“…This presentation of Time is dedicated to deterministic real time systems. When the value is equal to zero, then the corresponding transition is called immediate transition [19,25,33].…”

“…As an efficient formalism, the Petri Nets has proven its capacity to analyze the schedulability of an RTS [4,19,30,33,40]. Therefore, it is interesting to extend this formalism to analyze a partitioned RTS running on multiprocessor architecture.…”

States Graph Generation from dynamic Priority Time Petri Nets

“…This property is valid because the dPTPN deals with the conflict of enabled transitions problem via a dynamic calculus of priorities and only the transition with the highest value of priority is fired. Consequently, the dF T s contains only independent transitions [6,13] that can all be crossed together. The novel resulting marking is the combination of a collection of sub-states that can be created if each enabled transition is fired apart.…”

A FORMAL METHOD FOR SCHEDULING ANALYSIS OF A PARTITIONED MULTIPROCESSOR SYSTEM - Dynamic Priority Time Petri Nets

“…In this method, a priority is inserted on the input arcs of the dependent transitions (Kacem et al, 2010).Moreover, this method allows to master the complexity of the PTPN model by eliminating the use of another component, such as inhibitor arcs, to specify priorities. To control the size of the PTPN model, a hierarchical modeling was proposed in (Mahfoudhi et al, 2011).…”