Section: New Results

Diagnosis of large scale discrete event systems

Participants : Marie-Odile Cordier, Sophie Robin, Laurence Rozé, Yulong Zhao.

The problem we deal with is monitoring complex and large discrete-event systems (DES) such as an orchestration of web services or a fleet of mobile phones. Two approaches have been studied in our research group. The first one consists in representing the system model as a discrete-event system by an automaton. In this case, the diagnostic task consists in determining the trajectories (a sequence of states and events) compatible with the sequence of observations. From these trajectories, it is then easy to determine (identify and localize) the possible faults. In the second approach, the model consists in a set of predefined characteristic patterns. We use temporal patterns, called chronicles, represented by a set of temporally constrained events. The diagnostic task consists in recognizing these patterns by analyzing the flow of observed events.

Distributed monitoring with chronicles - Interleaving diagnosis and repair - Making web services more adaptive

Our work addresses the problem of maintaining the quality of service (QoS) of an orchestration of Web services (WS), which can be affected by exogenous events (i.e., faults). The main challenge in dealing with this problem is that typically the service where a failure is detected is not the one where a fault has occurred: faults have cascade effects on the whole orchestration of services. We have proposed a novel methodology to treat the problem that is not based on Web service (re)composition, but on an adaptive re-execution of the original orchestration. The re-execution process is driven by an orchestrator Manager that takes advantage of an abstract representation of the whole orchestration and may call a diagnostic module to localize the source of the detected failure. It is in charge of deciding the service activities whose results can be reused and may be skipped, and those that must be re-executed.

This year, we have improved the prototype and worked on a journal paper that will be submitted in 2013.

Scenario patterns for exploring qualitative ecosystems

This work aims at giving means of exploring complex systems, in our case ecosystems. We proposed to transform environmental questions about future evolution of ecosystems into formalized queries that can be submitted to a simulation model. The system behavior is represented as a discret event system described by a set of interacting timed automata, the global model corresponding to their composition on shared events. To query the model, we have defined high-level generic query patterns associated to the most usual types of request scenarios. These patterns are then translated into temporal logic formula. The answer is computed thanks to model-checking techniques that are efficient for analysing large-scale systems. Five generic patterns have been defined using TCTL (Timed Computation Tree Logic) “WhichStates”, “WhichDate”, “Stability”, “Always”, “Safety”. Three of them have been implemented using the model-checker UPPAAL.

The approach has been experimented on a marine ecosystem under fishing pressure. The model describes the trophodynamic interactions between fish trophic groups as well as interactions with the fishery activities and with an environmental context. A paper has been accepted for publication in the Environmental Modelling Software Journal [52] .

Controler synthesis for dealing with “How to” queries

We extended the approach to deal with “How to” queries. As before, we rely on a qualitative model in the form of timed automata and on model-checking tools to answer queries. We proposed and compared two approaches to answer questions such as “How to avoid a given situation ?”(safety query). The first one exploits controller synthesis and the second one is a “generate and test” approach. We evaluated these two approaches in the context of an application that motivates this work, i.e the management of a marine ecosystem and the evaluation of fishery management policies. The results have been accepted for publication in [17] .

More recently, we use similar methodological tools to model herd management on a catchment and analyse the best/optimal farming practices in order to reduce nitrate pollution due to livestock effluents. An hybrid model has been built using hierarchical timed automata. Scenarios can already be simulated and evaluated. We currently work on adapting controler synthesis tools in order to get the best strategies. This work is made in collaboration with our colleagues of Inra .