A methodology for detecting routing events in discrete flow networks

A theoretical framework for formulating and implementing model-based monitoring of discrete flow networks is discussed. Possible flows of items are described as the sequence of discrete-event (DE) traces. Each trace defines the DE sequence(s) that are triggered when an entity follows a given flow-path and visits tracking locations distributed within the monitored system. Given the set of possible discrete flows, a possible-behavior model - an interacting set of automata - is constructed, where each automaton models the discrete flow of items at each tracking location. Event labels or symbols contain all the information required to unambiguously distinguish each discrete flow. Within the possible behavior, there is a special sub-behavior whose occurrence is required to be detected. The special behavior may be specified by the occurrence of routing events, such as faults. These intermittent or non-persistent events may occur repeatedly. An observation mask is then defined, characterizing the actual observation configuration available for collecting item tracking data. The analysis task is then to determine whether this observation configuration is capable of detecting the identified special behavior. The assessment is accomplished by evaluating several observability notions, such as detectability and diagnosability. If the corresponding property is satisfied, associated formal observers are constructed to perform the monitoring task at hand. The synthesis of an optimal observation mask may also be conducted to suggest an appropriate observation configuration guaranteeing the detection of the special events and to construct associated monitoring agents. The proposed framework, modeling methodology, and supporting techniques for discrete flow networks monitoring are presented and illustrated with an example.