Agent technology is a software paradigm that permits to implement large and complex distributed applications. In order to assist the development of multi-agent systems, agent-oriented methodologies (AOM) have been created in the last years to support modeling more and more complex applications in many different domains. By defining in a non-ambiguous way concepts used in a specific domain, Meta modeling may represent a step towards such interoperability. In the Transport domain, this paper propose an agent-oriented meta-model that provides rigorous concepts for conducting transportation system problem modeling. The aim is to allow analysts to produce a transportation system model that precisely captures the knowledge of an organization so that an agent-oriented requirements specification of the system-to-be and its operational corporate environment can be derived from it. To this end, we extend and adapt an existing meta-model, Extended Gaia, to build a meta-model and an adequate model for transportation problems. Our new agent-oriented meta-model aims to allow the analyst to model and specify any transportation system as a multi-agent system. Based on the proposed meta-model, we proposes an approach for modeling and evaluating the Transportation System based on Stochastic Activity Network (SAN) components. The proposed process is based on seven steps from "Recognition" phase to "Quantitative Analysis" phase. These analyzes are based on the Dependability models which are built using the formalism Stochastic Activity Network. A real case study of Urban Public Transportation System has been conducted to show the benefits of the approach.
Formal methods, in particular the B Method and its extension Event-B are used to validate the system correct ness and to verify its properties. The weak point here is that Event-B that don't support quantitative analysis of performance and/or dependability. For this reason, we transform an Event-B specification to another formalism which automatically transform and allows us to evaluate the performance and/or dependability attributes. In this paper, we propose an algorithm which offers the transformation rules. This algorithm is implemented within our transformation tool, EventB2PN, to generate the transformation process from Event-B specification to Petri Net (PN) structure. EventB2PN tool use XML file for Event-B specification and stan dard PNML file for PN which can be analyzed with quantitative analysis tool. A small case study of repaired system has been conducted to show the benefits and the strong points in ours works.
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