Peer-to-peer systems have gained
momentum over the last years. This work was motivated by
the necessity to analyze such systems. It proposes a
distributed monitoring system, P2PMonitor, that has
alerters specialized in local monitoring of entities. These
alerters encode the basic events detected into streams of
(Active)XML documents. A method for filtering efficiently
such streams has been introduced. Also, an algorithm has
been proposed for the detection of parts of a new
monitoring task that are already supported by the system.
Complex and efficient stream processors are needed at the
heart of P2PMonitor. The work shows how to build them from
views over active documents and proposes a maintenance
algorithm that scales and reduces the computation time.
Modeling the applications is important for being able to
monitor them. At their origin, the business processes have
been mainly operation-centric, but recently, business
artifacts have been proposed and seem well adapted for the
specification of data-centric applications. The proposed
artifact model is based on active documents and captures:
their state, evolution, interactions and history.