Stefan Haar

Diagnosis of asynchronous discrete-event systems: a net unfolding approach

In this paper, we consider the diagnosis of asynchronous discrete event systems. We follow a so-called true concurrency approach, in which no global state and no global time is available. Instead, we use only local states in combination with a partial order model of time. Our basic mathematical tool is that of net unfoldings originating from the Petri net research area. This study was motivated by the problem of event correlation in telecommunications network management.

Probabilistic QoS and Soft Contracts for Transaction-Based Web Services Orchestrations

Service level agreements (SLAs), or contracts, have an important role in Web services. They define the obligations and rights between the provider of a Web service and its client, about the function and the quality of the service (QoS). For composite services like orchestrations, contracts are deduced by a process called QoS contract composition, based on contracts established between the orchestration and the called Web services. Contracts are typically stated as hard guarantees (e.g., response time always less than 5 msec). Using hard bounds is not realistic, however, and more statistical approaches are needed. In this paper we propose using soft probabilistic contracts instead, which consist of a probability distribution for the considered QoS parameter-in this paper, we focus on timing. We show how to compose such contracts, to yield a global probabilistic contract for the orchestration. Our approach is implemented by the TOrQuE tool. Experiments on TOrQuE show that overly pessimistic contracts can be avoided and significant room for safe overbooking exists. An essential component of SLA management is then the continuous monitoring of the performance of called Web services, to check for violations of the SLA. We propose a statistical technique for run-time monitoring of soft contracts.

Distributed Monitoring of Concurrent and Asynchronous Systems

In this paper we study the diagnosis of distributed asynchronous systems with concurrency. Diagnosis is performed by a peer-to-peer distributed architecture of supervisors. Our approach relies on Petri net unfoldings and event structures, as means to manipulate trajectories of systems with concurrency. This article is an extended version of the paper with same title, which appeared as a plenary address in the Proceedings of CONCUR’2003.

Markov nets: probabilistic models for distributed and concurrent systems

For distributed systems, i.e., large complex networked systems, there is a drastic difference between a local view and knowledge of the system, and its global view. Distributed systems have local state and time, but do not possess global state and time in the usual sense. In this paper, motivated by the monitoring of distributed systems and in particular of telecommunications networks, we develop a generalization of Markov chains and hidden Markov models for distributed and concurrent systems. By a concurrent system, we mean a system in which components may evolve independently, with sparse synchronizations. We follow a so-called true concurrency approach, in which neither global state nor global time are available. Instead, we use only local states in combination with a partial order model of time. Our basic mathematical tool is that of Petri net unfoldings.

Diagnosis of asynchronous discrete event systems: datalog to the rescue!

We consider query optimization techniques for data intensive P2P applications. We show how to adapt an old technique from deductive databases, namely Query-Sub-Query (QSQ), to a setting where autonomous and distributed peers share large volumes of interelated data.We illustrate the technique with an important telecommunication problem, the diagnosis of distributed telecom systems. We show that (i) the problem can be modeled using Datalog programs, and (ii) it can benefit from the large battery of optimization techniques developed for Datalog. In particular, we show that a simple generic use of the extension of QSQ achieves an optimization as good as that previously provided by dedicated diagnosis algorithms. Furthermore, we show that it allows solving efficiently a much larger class of system analysis problems.

Diagnosis of asynchronous discrete event systems, a net unfolding approach

This paper studies the diagnosis of asynchronous discrete event systems. We follow a so-called true concurrency approach, in which neither the global state nor global time are available. Instead, we use only local states in combination with a partial order model of time; our basic mathematical tool is that of Petri net unfoldings. This study was motivated by the problem of event correlation in telecommunications network management.

Probabilistic QoS and soft contracts for transaction based Web services

Service level agreements (SLAs), or contracts, have an important role in Web services. They define the obligations and rights between the provider of a Web service and its client, about the function and the quality of the service (QoS). For composite services like orchestrations, contracts are deduced by a process called QoS contract composition, based on contracts established between the orchestration and the called Web services. Contracts are typically stated as hard guarantees (e.g., response time always less than 5 msec). Using hard bounds is not realistic, however, and more statistical approaches are needed. In this paper we propose using soft probabilistic contracts instead, which consist of a probability distribution for the considered QoS parameter-in this paper, we focus on timing. We show how to compose such contracts, to yield a global probabilistic contract for the orchestration. Our approach is implemented by the TOrQuE tool. Experiments on TOrQuE show that overly pessimistic contracts can be avoided and significant room for safe overbooking exists. An essential component of SLA management is then the continuous monitoring of the performance of called Web services, to check for violations of the SLA. We propose a statistical technique for run-time monitoring of soft contracts.

Testing input/output partial order automata

We propose an extension of the Finite State Machine framework in distributed systems, using input/output partial order automata (IOPOA). In this model, transitions can be executed non-atomically, reacting to asynchronous inputs on several ports, and producing asynchronous output on those ports. We develop the formal framework for distributed testing in this architecture and compare with the synchronous I/O automaton setting. The advantage of the compact modelling by IOPOA combines with low complexity : the number of tests required for concurrent input in our model is polynomial in the number of inputs.

Testing Systems Specified as Partial Order Input/Output Automata

An Input/Output Automaton is an automaton with a finite number of states where each transition is associated with a single inpu f or output interaction. In [1], we introduced a new formalism, in which each transition is associated with a bipartite partially ordered set made of concurrent inputs followed by concurrent outputs. In this paper, we generalize this model to Partial Order Input/Output Automata (POIOA), in which each transition is associated with an almost arbitrary partially ordered set of inputs and outputs. This formalism can be seen as High-Level Messages Sequence Charts with inputs and outputs and allows for the specification of concurrency between inputs and outputs in a very general, direct and concise way. We give a formal definition of this framework, and define several conformance relations for comparing system specifications expressed in this formalism. Then we show how to derive a test suite that guarantees to detect faults defined by a POIOA-specific fault model: missing output faults, unspecified output faults, weaker precondition faults, stronger precondition faults and transfer faults.

Types of Asynchronous Diagnosability and the Reveals-Relation in Occurrence Nets

We consider asynchronous diagnosis in (safe) Petri net models of distributed systems, using the partial order semantics of occurrence net unfoldings. Both the observability and diagnosability properties will appear in two different forms, depending on the semantics chosen: strong observability and diagnosability are the classical notions from the state machine model and correspond to interleaving semantics in Petri nets. By contrast, the weak form is linked to characteristics of nonsequential processes, and requires an asynchronous progress assumption on those processes. We give algebraic characterizations for both types, and give verification methods. The study of weak diagnosability leads us to the analysis of a relation in occurrence nets, first presented in : given the occurrence of some event a that reveals b, the occurrence of b is inevitable. Then b may already have occurred, be concurrent to, or even in the future of a. We show that the reveals-relation can be effectively computed recursively-for each pair, a suitable finite prefix of bounded depth is sufficient-, and show its use in asynchronous diagnosis. Based on this relation, a decomposition of the Petri net unfolding into facets is defined, yielding an abstraction technique that preserves and reflects maximal partially ordered runs.