Tuesday, January 15, 2008

On situations

Hello from Zurich, got here in a train from Munich - and this is the famous train station of Zurich (in light), I have arrived in the dark, but has been in Zurich quite a lot of times before, tomorrow I am visiting the IBM Zurich Lab (which is actually located in Rüschlikon (a suburb of Zurich) home to four Noble prizes in physics. The hotel is 5 minutes walk from the train, but I forgot to print a map, and had to search a little. In the first half of the day I have participated in the continuation of the CITT conference, and earned my bread by giving a talk. After the talk I had some discussion with people about the term situation that I mentioned in the talk. I have borrowed this word from "situation calculus" in AI, and it fits well with terms in related domain such as: situation awareness. The discussion has been has been around one of the common misconceptions that situation is an alias to derived event. The answer is - no, these terms are not aliases ! Situation is some phenomenon that requires reaction (or notification). It is in the conceptual ontology of the consumer. Now - let's check the relationships with event:

(1). A raw event that is reported by a producer is a situation in the consumer's terms - in this case, only routing is required ("simple event processing").

(2). A raw event is reported by a producer has 1-1 correspodence to a situation in the consumer's terms, but more information or translation is required - in this case, the situation is created by mediated event processing.

(3). The situation occurs in a deterministic way once an event pattern is identified, and it is a functions of the events participating in the pattern - in this case the situation is created by complex event processing.

Note that the situation is not the derived event - but the derived event in this case is an indication that the situation is detected, note also that not all derived events are situations, derived events that are consumed by other agents, are not situations, only those that are consumed by event consumers.

However, situation detection may not be purely deterministic - and here we are getting to "intelligent event processing". Example: the pattern is only an approximation, example: the pattern is - "an event E1 happens at least 4 times within an hour". Now, if the event E1 happens 3 times and the pattern is an approximation, there is some probability that the situation did occur. This is even before looking at probabilistic events.

More about uncertainty in event processing - later.

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