Distributed Monitoring of Peer-to-Peer Systems (demo)

International audienceObserving highly dynamic Peer-to-Peer systems is essential for many applications such as fault management or business processing. We demonstrate P2PMonitor, a P2P system for monitoring such systems. Alerters deployed on the monitored peers are designed to detect particular kinds of local events. They generate streams of XML data that form the primary sources of information for P2PMonitor. The core of the system is composed of processing components implementing the operators of an algebra over data streams. From a user viewpoint, monitoring a P2P system can be as simple as querying an XML document. The document is an ActiveXML document that aggregates a (possibly very large) number of streams generated by alerters on the monitored peers. Behind the scene, P2PMonitor compiles the monitoring query into a distributed monitoring plan, deploys alerters and stream algebra processors and issues notifications that are sent to users. The system functionalities are demonstrated by simulating the supply chain of a large company

The AXML Artifact Model

International audienceTowards a data-centric workflow approach, we introduce an artifact model to capture data and workflow management activities in distributed settings. The model is built on Active XML, i.e., XML trees including Web service calls. We argue that the model captures the essential features of business artifacts as described informally in [1] or discussed in [2]. To illustrate, we briefly consider the monitoring of distributed systems and the verification of temporal properties for them

Distributed Monitoring of Peer to Peer Systems

International audienceIn this paper, we are concerned with the distributed monitoring of P2P systems. We introduce the P2P Monitor system and a new declarative language, namely P2PML, for specifying monitoring tasks. A P2PML subscription is compiled into a distributed algebraic plan which is described using algebra over XML streams. The operators of this algebra are first alerters in charge of detecting specific events and acting as stream sources. Other operators process the streams or publish them. We introduce a filter for streams of XML documents that scales by processing first simple conditions and then, if still needed, evaluating complex queries. We also show how particular tasks can be supported by identifying subtasks that are already provided by existing streams