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Observation Strategies for Event Detection with Incidence on Runtime Verification: Theory, Algorithms, Experimentation
August 2011
rcra2010-amai
Many applications (such as system and user monitoring, runtime verification, diagnosis, observation-based decision making, intention recognition) all require to detect the occurrence of an event in a system, which entails the ability to observe the system. Observation can be costly, so it makes sense to try and reduce the number of observations, without losing full certainty about the event's actual occurrence. In this paper, we propose a formalization of this problem. We formally show that, whenever the event to be detected follows a discrete spatial or temporal pattern, then it is possible to reduce the number of observations. We discuss exact and approximate algorithms to solve the problem, and provide an experimental evaluation of them. We apply the resulting algorithms to verification of linear temporal logics formulae. We discuss possible generalizations and extensions, and, in particular, how event detection can benefit from logic programming techniques.
Journal
Marco Alberti, P. Dell'Acqua, Luís Moniz Pereira
Annals of Mathematics and Artificial Intelligence
Springer
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DOI: 10.1007/s10472-011-9259-5
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1573-7470
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http://centria.di.fct.unl.pt/~lmp/publications/online-papers/runtime_verification_amai.pdf
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Marco Alberti and P. Dell'Acqua and Luís Moniz Pereira, Observation Strategies for Event Detection with Incidence on Runtime Verification: Theory, Algorithms, Experimentation, Annals of Mathematics and Artificial Intelligence, Pag. DOI: 10.1007/s10472-011-9259-5, Springer, ISSN 1573-7470, (http://centria.di.fct.unl.pt/~lmp/publications/online-papers/runtime_verification_amai.pdf), August 2011.
<b><a href="/people/members/view.php?code=bde07d722513741a0fa20a19209bc4a1" class="author">Marco Alberti</a>, <a href="/people/members/view.php?code=c3899b9bc15364381381c58d138af552" class="author">P. Dell'Acqua</a> and <a href="/people/members/view.php?code=6175f826202ff877fba2ad77784cb9cb" class="author">Luís Moniz Pereira</a></b>, <u>Observation Strategies for Event Detection with Incidence on Runtime Verification: Theory, Algorithms, Experimentation</u>, Annals of Mathematics and Artificial Intelligence, Pag. DOI: 10.1007/s10472-011-9259-5, <a href="http://www.springer.com" title="Link to external entity..." target="_blank" class="publisher">Springer</a>, ISSN 1573-7470, (<a href="http://centria.di.fct.unl.pt/~lmp/publications/online-papers/runtime_verification_amai.pdf" target="_blank">url</a>), August 2011.
@article {rcra2010-amai, author = {Marco Alberti and P. Dell'Acqua and Lu\'{\i}s Moniz Pereira}, title = {Observation Strategies for Event Detection with Incidence on Runtime Verification: Theory, Algorithms, Experimentation}, journal = {Annals of Mathematics and Artificial Intelligence}, publisher = {Springer}, pages = {DOI: 10.1007/s10472-011-9259-5}, issn = {1573-7470}, url = {http://centria.di.fct.unl.pt/~lmp/publications/online-papers/runtime_verification_amai.pdf}, abstract = {Many applications (such as system and user monitoring, runtime verification, diagnosis, observation-based decision making, intention recognition) all require to detect the occurrence of an event in a system, which entails the ability to observe the system. Observation can be costly, so it makes sense to try and reduce the number of observations, without losing full certainty about the event's actual occurrence. In this paper, we propose a formalization of this problem. We formally show that, whenever the event to be detected follows a discrete spatial or temporal pattern, then it is possible to reduce the number of observations. We discuss exact and approximate algorithms to solve the problem, and provide an experimental evaluation of them. We apply the resulting algorithms to verification of linear temporal logics formulae. We discuss possible generalizations and extensions, and, in particular, how event detection can benefit from logic programming techniques.}, keywords = {Event detection · Runtime verification · Temporal logic · Logic programming · Complexity}, month = {August}, year = {2011}, }
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