Section: New Results

Management of large distributed systems

Distributed optimal planning

Participant : Éric Fabre.

Planning problems consist in organizing actions in a system in order to reach one of some target states. The actions consume and produce resources, can of course take place concurrently, and may have costs. We have a collection of results addressing this problem in the setting of distributed systems. This takes the shape of a network of components, each one holding private actions operating over its own resources, and shared/synchronized actions that can only occur in agreement with its neighbors. The goal is to design in a distributed manner a tuple of local plans, one per component, such that their combination forms a consistent global plan of minimal cost.

Our previous solutions to this problem modeled components as weighted automata. In collaboration with Loig Jezequel (TU Munich) and Victor Khomenko (Univ. of Newcastle), we have extended this approach to the case of components modeled as safe Petri nets  [50] . This allows one to benefit from the internal concurrency of actions within a component. Benchmarks have shown that this method can lead to significant time reductions to find feasible plans, in good cases. In the least favorable cases, performances are comparable to those obtained with components modeled as automata. The method does not apply to all situations however, as computations require to perform $ϵ$-reductions on Petri-nets (our work also contains a contribution to this difficult question). This work has been accepted by the ACM Transactions in Embedded Computing Systems, to appear in 2015.