### Joost-Pieter Katoen On The Need for Probabilistic and Stochastic Modelling

I am posting this message on behalf of Joost-Pieter Katoen, who sent me his reaction to one of the questions posed to the panel members during our workshop at CONCUR 2007. Enjoy!

I'd like to answer to the question on the need for stochastic and probabilistic modeling (and analysis). Some concrete examples of case studies provided by industry for which probabilistic aspects are very important are listed below. The importance of explicitly modeling random effects explicitly stands or falls with the kind of property to be established, of course, so I am definitely not claiming that these examples cannot (and should not) be modeled by techniques that do not support random phenomena.

1. Leader election in IEEE 1394: in case of a conflict (two nodes

pretend to be a leader), the contending nodes send a message (be

my parent) and randomly wait either short or long. What is the

optimal policy to resolve the contention the fastest? (This turns

out to be a slightly unbiased coin).

2. In the Ametist EU-project, the German industrial partner Axxom

generated schedules for a lacquer production plant. While doing

so, they abstracted from many details that the lacquer producer

supplies such as: the average fraction of time a resource is not

operational, the fraction of (operational) time the resource can

be used because necessary human support is present, and so

forth. In their abstraction they scheduled tasks conservatively

and they were interested in whether they could improve their

schedules while reducing the probability to miss the deadline.

Clearly, a stochastic modeling is needed, and indeed has been

carried out using a stochastic process algebra.

3. Hubert and Holger should be able to say much more about

a recent project they are pursuing with a French company on

the validation of multiprocessor multi-threaded architectures.

I do not know exactly what they are investigating, but they use

stochastic process algebras to model!

Finally, let me say that (as Moshe is also indicating) that the

interest in probabilistic modeling is growing steadily. To give

an example, the European Space Agency (ESA) is currently

considering to use probabilistic modeling and analysis in the

context of AADL, an architecture specification language where

an important ingredient ais the failure rates of components.

All in all, it is fair to say that there is a quest for probabilistic

techniques!

Joost-Pieter Katoen

I'd like to answer to the question on the need for stochastic and probabilistic modeling (and analysis). Some concrete examples of case studies provided by industry for which probabilistic aspects are very important are listed below. The importance of explicitly modeling random effects explicitly stands or falls with the kind of property to be established, of course, so I am definitely not claiming that these examples cannot (and should not) be modeled by techniques that do not support random phenomena.

1. Leader election in IEEE 1394: in case of a conflict (two nodes

pretend to be a leader), the contending nodes send a message (be

my parent) and randomly wait either short or long. What is the

optimal policy to resolve the contention the fastest? (This turns

out to be a slightly unbiased coin).

2. In the Ametist EU-project, the German industrial partner Axxom

generated schedules for a lacquer production plant. While doing

so, they abstracted from many details that the lacquer producer

supplies such as: the average fraction of time a resource is not

operational, the fraction of (operational) time the resource can

be used because necessary human support is present, and so

forth. In their abstraction they scheduled tasks conservatively

and they were interested in whether they could improve their

schedules while reducing the probability to miss the deadline.

Clearly, a stochastic modeling is needed, and indeed has been

carried out using a stochastic process algebra.

3. Hubert and Holger should be able to say much more about

a recent project they are pursuing with a French company on

the validation of multiprocessor multi-threaded architectures.

I do not know exactly what they are investigating, but they use

stochastic process algebras to model!

Finally, let me say that (as Moshe is also indicating) that the

interest in probabilistic modeling is growing steadily. To give

an example, the European Space Agency (ESA) is currently

considering to use probabilistic modeling and analysis in the

context of AADL, an architecture specification language where

an important ingredient ais the failure rates of components.

All in all, it is fair to say that there is a quest for probabilistic

techniques!

Joost-Pieter Katoen

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