An Overture to the 2007 CEP Blog Awards

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Old 01-09-2008
An Overture to the 2007 CEP Blog Awards

Tim Bass
Wed, 09 Jan 2008 11:09:46 +0000

Before announcing the winners of the 2007 CEP Blog Awards I thought it would be helpful to introduce the award categories to our readers.
I have given considerable thought to how to structure The CEP Blog Awards.** This was not an easy task, as*you might imagine,*given the confusion in the event processing marketspace.** So here goes.
For the 2007 CEP*Blog Awards*I have created three*event processing categories.** Here are the categories and a brief description of each one:
The CEP Blog Award for*Rule-Based Event Processing
Preface:***I was also inclined to call this category “process-based*event processing” or “control-based event processing”*and might actually do so in the future.** As always, your comments and feedback are important and appreciated.
Rule-based* (or process-based) event processing is a major subcategory of event processing.*****Rule-based approaches to event processing are very useful for stateful event-driven process control,* track and trace, dynamic resource management and basic pattern detection (see slide 12 of this presentation).** Rule-based approaches are optimal for a wide-range of production-related event processing systems.*
However, just like any system, there are engineering trade-offs using this approach.* Rule-based systems tend not to scale well when the number of rules (facts) are large.* Rule-based approaches can also be difficult to manage in a distributed multi-designer environment.* Moreover, rule-based*approaches are suboptimal for self-learning and*tend not*to*process uncertaintly very well.* Never the less, rule-based event processing is a very important* CEP category.
The CEP Blog Award for Event Stream Processing
Stream-centric approaches to event processing are also a very important overall category of event processing.* Unlike a stateful, process-driven rule-based approach, event stream processing optimizes high performance continuous queries over sliding time windows.* High performance, low*latency event processing*is one of the main design goals for many stream processing engines.*
Continuous queries over event streams are genenerally designed to be*executed in milliseconds, seconds and perhaps a bit*longer time intervals.** Process-driven event processing, on the other hand, can manage processes, resources, states and patterns over* long time intervals,*for example,*hours and days, not*just milliseconds and seconds.**
Therefore, event stream processing*tends to be*optimized for a different set of problems than process-based (which I am calling rule-based this year) event processing.* Similar to rule or process-based approaches, most current stream processing engines do not manage or deal with probability, likelihood*and uncertainty very well (if at all).
The CEP*Blog Award* for Advanced Event Processing
For a lack of a better term, I call this category advanced event processing.** Advanced event processing*will more-than-likely*have a rule-based and/or a stream-based event processing component.** However, to be categorized as advanced event processing software the software platform must also be able to perform more advanced event processing that can deal with probability, fuzzy logic and/or*uncertainty.** Event processing software in this category should also have the capability to automatically learn, or be trained, similar to artifical neural networks.**
Some of my good colleagues*might prefer to call this category AI-capable event processing (or intelligent event processing), but I prefer to call this award category advanced event processing for the 2007 awards.* If you like the term intelligent event processing, let’s talk about this in 2008!
Ideally, advanced event processing software should have plug-in modules that permit the event processing architect, or systems programmer, to select and configure*one or more different analytical methods at design-time.*** The results from one method should be available to other methods, for example the output of a stream processing module*might be the input to a neural network (NN)*or Bayesian Belief (BN)*module.** In another example pipeline operation, the output of a Bayesian classifier*could*be the input to a process or rule-based event processing module within the same run-time environment.
For all three categories for 2007, there should be a graphical user interface for design-time construction and modeling.*** There should also be a robust run-time environment and most, if*not all, *of the other “goodies” that we expect from event processing platforms.
Most importantly, there should be reference customers for the software and the company.**** The CEP Blog Awards will be only given to companies with a proven and public*customer base.
In my next post on this topic, I’ll name the Awardees for 2008.**** Thank you for standing by.* If you have any questions or comments, please contact me directly.
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