Freshness-aware metadata management: Performance evaluation with SWN models

Recent systems which are in general composed by several resources and distributed over a large-scale network, need high-level models to be studied. In these complex systems such as peer-to-peer systems, efficient and fast query routing is necessary for managing applications workload. Many works have been proposed to deal with query routing, however none of these studies rely on Stochastic Well formed Petri Nets (SWN) for modelling the approach proposed. We aim in this paper, to propose an algorithm for managing metadata needed to route queries. Moreover we use SWN models to evaluate and validate our approach. Our solution is freshness-aware, thus gains in the fact that stale data can be read under some limits. These limits are wideley taken into account for managing metadata coherently. Our study takes into account the concurrency, the synchronization, the parallelism, the identity of the resources and their cooperation. We propose two SWN models for structuring metadata: one with strong consistency and another with weak consistency. Simulations are used to validate our approach and the results obtainded demonstrate the fesability of our solution.