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Laurence Duchien - One of the best experts on this subject based on the ideXlab platform.
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Undoing Event-Driven Adaptation of Business Processes
2011Co-Authors: Sébastien Mosser, Gabriel Hermosillo, Lionel Seinturier, Anne-françoise Le Meur, Laurence DuchienAbstract:As business Processes continue to gain relevance in different domains, dynamicity is becoming a great con- cern. Static Processes no longer cover the actual needs of constantly changing environments, and Process Adaptation is a must in order to maintain competitive levels. While creating dynamically adaptable business Processes can be a challenging task, undoing these Adaptations is a natural functionality that has not been studied in depth. Straight forward approaches for unAdaptation can easily end up with corrupted Processes, bringing uncertainty to the whole business logic. In this paper we bring forward a solution for efficiently undoing a business Process Adaptation in event-driven environments, considering also the correlated Adaptations that happened afterwards.
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IEEE SCC - Undoing Event-Driven Adaptation of Business Processes
2011 IEEE International Conference on Services Computing, 2011Co-Authors: Sébastien Mosser, Gabriel Hermosillo, Lionel Seinturier, Anne-françoise Le Meur, Laurence DuchienAbstract:As business Processes continue to gain relevance in different domains, dynamicity is becoming a great concern. Static Processes no longer cover the actual needs of constantly changing environments, and Process Adaptation is a must in order to maintain competitive levels. While creating dynamically adaptable business Processes can be a challenging task, undoing these Adaptations is a natural functionality that has not been studied in depth. Straight forward approaches for unAdaptation can easily end up with corrupted Processes, bringing uncertainty to the whole business logic. In this paper we bring forward a solution for efficiently undoing a business Process Adaptation in event-driven environments, considering also the correlated Adaptations that happened afterwards.
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Creating Context-Adaptive Business Processes
2010Co-Authors: Gabriel Hermosillo, Lionel Seinturier, Laurence DuchienAbstract:As the dynamicity of today's business environments keeps increasing, there is a need to continuously adapt business Processes in order to respond to the changes in those environments and keep a competitive level. By using complex event Processing, we can discover information that is relevant to our organization, which is usually hidden among the data generated in the environment, and use it to adapt the Processes accordingly in order to respond to the changing conditions in an optimal way. Unfortunately, the static nature of business Process definitions makes it impossible to adapt them at runtime and the redeployment of a modified Process is required. By using a component-based approach, we can transform the existing business Processes into dynamically bound components, adding the flexibility needed to adapt the Processes at runtime. In this paper we present CEVICHE, a framework that combines the strengths of complex event Processing and dynamic business Process Adaptation, which allows to respond to the needs of the rapidly changing environment, and its Adaptation language called SBPL, an extension to BPEL which adds flexibility to business Processes.
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Using Complex Event Processing for Dynamic Business Process Adaptation
2010Co-Authors: Gabriel Hermosillo, Lionel Seinturier, Laurence DuchienAbstract:As the amount of data generated by today's pervasive environments increases exponentially, there is a stronger need to decipher the important information that is hidden among it. By using complex event Processing, we can obtain the information that really matters to our organization and use it to improve our Processes. However, even when this information is retrieved, business Processes remain static and cannot be changed dynamically to adapt to the actual scenario, diminishing the advantages that can be achieved. In this paper we present CEVICHE, a framework that combines the strengths of complex event Processing and dynamic business Process Adaptation, which allows to respond to the needs of today's rapidly changing environments. We use a simple car rental scenario to show how CEVICHE could be used to maintain the quality of service of a business Process by adapting it according to the situation.
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IEEE SCC - Using Complex Event Processing for Dynamic Business Process Adaptation
2010 IEEE International Conference on Services Computing, 2010Co-Authors: Gabriel Hermosillo, Lionel Seinturier, Laurence DuchienAbstract:As the amount of data generated by today's pervasive environments increases exponentially, there is a stronger need to decipher the important information that is hidden among it. By using complex event Processing, we can obtain the information that really matters to our organization and use it to improve our Processes. However, even when this information is retrieved, business Processes remain static and cannot be changed dynamically to adapt to the actual scenario, diminishing the advantages that can be achieved. In this paper we present CEVICHE, a framework that combines the strengths of complex event Processing and dynamic business Process Adaptation, which allows to respond to the needs of today's rapidly changing environments. We use a simple car rental scenario to show how CEVICHE could be used to maintain the quality of service of a business Process by adapting it according to the situation.
Flavia Maria Santoro - One of the best experts on this subject based on the ideXlab platform.
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Real-Time Process Adaptation: A Context-Aware Replanning Approach
IEEE Transactions on Systems Man and Cybernetics: Systems, 2018Co-Authors: Vanessa Nunes, Claudia Werner, Flavia Maria Santoro, Célia Ghedini RalhaAbstract:Complexity and dynamism of day-to-day activities are inextricably linked, thus the need for constant Adaptation to address emerging demands has grown. Process Adaptation is the action of customizing a Process instance to make it applicable to a particular situation. However, unplanned conditions may occur at any time during Process execution. So, the design of a complete Process model has given place to a flexible design based on reuse and Adaptation. This paper addresses the problem of dynamic Adaptation within a Process-aware information system (IS). On top of a theory for context-aware ISs, we argue that an unexpected situation can be characterized by a number of known contextual elements and could be used to automate the decision of replanning the Process flow in a specific instance, in order to preserve the Process strategy. The solution was evaluated in real setting observational studies in the domains of oil and gas and air traffic control.
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A method to infer the need to update situations in business Process Adaptation
Computers in Industry, 2015Co-Authors: Juliana Do E. Santo Carvalho, Flavia Maria Santoro, Kate RevoredoAbstract:A method to learn situations that influence a business Process execution.The results from two case studies in the Air Traffic Control domain.Evidences of the impact of context changes in business Process over time.Potential to learn with the dynamicity of context through the method proposed. Contextual knowledge is an essential resource for adapting business Processes in order to keep them aligned with its goals. A context-based Adaptation environment should learn from the dynamism of the context as well as the decisions made, and continuously identify new unforeseen situations. Data mining is a possibility to maintain the analysis of the Processes updated. This paper presents a method that infers the need to learn new situations that influence a business Process execution. The method is based on the results of the Apriori algorithm application. Case studies were conducted to evaluate the proposal. We observed evidences of context changes over time and the potential to learn with this dynamics through the method proposed.
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CSCWD - Mediating Process Adaptation through a goal-oriented context-aware approach
Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2012Co-Authors: Vanessa Nunes, Claudia Werner, Flavia Maria SantoroAbstract:Complexity and dynamism of day-to-day activities in organizations are inextricably linked, one impacting the other, increasing the challenges for constant Adaptation on the way to organize work to address emerging demands. Market is demanding systems that are aware of organizations Processes and able to evolve and adapt to new situations in everyday working activities. We argue that flexibility in Processes could be managed in real time, by PAIS (Process-aware Information Systems), using context information collected in the work environment. This paper proposes CGAdapt, a context management architecture approach that aims to improve and automate dynamic Process Adaptation. We explain how Process Adaptation may occur in real time through an existent scenario using this proposal and discuss the value of context-awareness to reason about Process alternative Adaptations in a goal oriented approach.
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dynamic Process Adaptation a context aware approach
Computer Supported Cooperative Work in Design, 2011Co-Authors: Vanessa Tavares Nunes, Claudia Werner, Flavia Maria SantoroAbstract:Dynamism of day-to-day activities in organizations is inextricably linked and there is a variety of information, insight and reasoning being Processed between people and systems, in carrying out a business Process. We argue that flexibility in Processes could be managed in real time, using context information collected in the work environment. This paper proposes a context management architecture approach that aims to improve and automate dynamic Process Adaptation. We explain how Process Adaptation may occur in real time and discuss a scenario for this proposal
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CSCWD - Dynamic Process Adaptation: A context-aware approach
Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2011Co-Authors: Vanessa Nunes, Claudia Werner, Flavia Maria SantoroAbstract:Dynamism of day-to-day activities in organizations is inextricably linked and there is a variety of information, insight and reasoning being Processed between people and systems, in carrying out a business Process. We argue that flexibility in Processes could be managed in real time, using context information collected in the work environment. This paper proposes a context management architecture approach that aims to improve and automate dynamic Process Adaptation. We explain how Process Adaptation may occur in real time and discuss a scenario for this proposal
Andreas Metzger - One of the best experts on this subject based on the ideXlab platform.
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BPM - Triggering Proactive Business Process Adaptations via Online Reinforcement Learning
Lecture Notes in Computer Science, 2020Co-Authors: Andreas Metzger, Tristan Kley, Alexander PalmAbstract:Proactive Process Adaptation can prevent and mitigate upcoming problems during Process execution by using predictions about how an ongoing case will unfold. There is an important trade-off with respect to these predictions: Earlier predictions leave more time for Adaptations than later predictions, but earlier predictions typically exhibit a lower accuracy than later predictions, because not much information about the ongoing case is available. An emerging solution to address this trade-off is to continuously generate predictions and only trigger proactive Adaptations when prediction reliability is greater than a predefined threshold. However, a good threshold is not known a priori. One solution is to empirically determine the threshold using a subset of the training data. While an empirical threshold may be optimal for the training data used and the given cost structure, such a threshold may not be optimal over time due to non-stationarity of Process environments, data, and cost structures. Here, we use online reinforcement learning as an alternative solution to learn when to trigger proactive Process Adaptations based on the predictions and their reliability at run time. Experimental results for three public data sets indicate that our approach may on average lead to 12.2% lower Process execution costs compared to empirical thresholding.
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CAiSE - Proactive Process Adaptation Using Deep Learning Ensembles
Advanced Information Systems Engineering, 2019Co-Authors: Andreas Metzger, Philipp Bohn, Adrian Neubauer, Klaus PohlAbstract:Proactive Process Adaptation can prevent and mitigate upcoming problems during Process execution. Proactive Adaptation decisions are based on predictions about how an ongoing Process instance will unfold up to its completion. On the one hand, these predictions must have high accuracy, as, for instance, false negative predictions mean that necessary Adaptations are missed. On the other hand, these predictions should be produced early during Process execution, as this leaves more time for Adaptations, which typically have non-negligible latencies. However, there is an important tradeoff between prediction accuracy and earliness. Later predictions typically have a higher accuracy, because more information about the ongoing Process instance is available. To address this tradeoff, we use an ensemble of deep learning models that can produce predictions at arbitrary points during Process execution and that provides reliability estimates for each prediction. We use these reliability estimates to dynamically determine the earliest prediction with sufficient accuracy, which is used as basis for proactive Adaptation. Experimental results indicate that our dynamic approach may offer cost savings of 27% on average when compared to using a static prediction point.
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ICSOC - Risk-Based Proactive Process Adaptation
Service-Oriented Computing, 2017Co-Authors: Andreas Metzger, Philipp BohnAbstract:Proactive Process Adaptation facilitates preventing or mitigating upcoming problems during Process execution, such as Process delays. Key for proactive Process Adaptation is that Adaptation decisions are based on accurate predictions of problems. Previous research focused on improving aggregate accuracy, such as precision or recall. However, aggregate accuracy provides little information about the error of an individual prediction. In contrast, so called reliability estimates provide such additional information. Previous work has shown that considering reliability estimates can improve decision making during proactive Process Adaptation and can lead to cost savings. So far, only constant cost functions have been considered. In practice, however, costs may differ depending on the magnitude of the problem; e.g., a longer Process delay may result in higher penalties. To capture different cost functions, we exploit numeric predictions computed from ensembles of regression models. We combine reliability estimates and predicted costs to quantify the risk of a problem, i.e., its probability and its severity. Proactive Adaptations are triggered if risks are above a pre-defined threshold. A comparative evaluation indicates that cost savings of up to 31%, with 14.8% savings on average, may be achieved by the risk-based approach.
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CAiSE - Predictive Business Process Monitoring Considering Reliability Estimates
Advanced Information Systems Engineering, 2017Co-Authors: Andreas Metzger, Felix FöckerAbstract:Predictive business Process monitoring aims at predicting potential problems during Process execution so that these problems can be proactively managed and mitigated. Compared to aggregate prediction accuracy indicators (e.g., precision or recall), prediction reliability estimates provide additional information about the prediction error for an individual business Process. Intuitively, it appears appealing to consider reliability estimates when deciding on whether to adapt a running Process instance or not. However, we lack empirical evidence to support this intuition, as research on predictive business Process monitoring focused on aggregate prediction accuracy. We experimentally analyze the effect of considering prediction reliability estimates for proactive business Process Adaptation. We use ensemble prediction techniques, which we apply to an industry data set from the transport and logistics domain. In our experiments, proactive business Process Adaptation in general had a positive effect on cost in 52.5% of the situations. In 82.9% of these situations, considering reliability estimates increased the positive effect, leading to cost savings of up to 54%, with 14% savings on average.
Gregoris Mentzas - One of the best experts on this subject based on the ideXlab platform.
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Assessing Flexibility in Event-Driven Process Adaptation
Information Systems, 2019Co-Authors: Ioannis Patiniotakis, Dimitris Apostolou, Yiannis Verginadis, Nikos Papageorgiou, Gregoris MentzasAbstract:Abstract Business Process management (BPM) has emerged as a prominent information management approach focusing on the design, execution and governance of organizational business Processes. The ability to deal with both foreseen and unforeseen changes in business Processes is considered critical for contemporary business Process management systems. This paper proposes an approach that couples an event-driven framework for detecting and reasoning in situations that pose the need for Process Adaptations with MCDM methods for selecting Adaptations. The proposed approach has been implemented in an aspect-oriented extension of a BPMN2.0 engine in order to enact Adaptations of business Processes in real-time.
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Business Process Management Workshops - An Aspect Oriented Approach for Implementing Situational Driven Adaptation of BPMN2.0 Workflows
Business Process Management Workshops, 2013Co-Authors: Ioannis Patiniotakis, Dimitris Apostolou, Yiannis Verginadis, Nikos Papageorgiou, Gregoris MentzasAbstract:To address the issue of business Process Adaptation, we focus on handling Adaptation needs as cross-cutting concerns because they rely or must affect many parts of a business Process. Our research objective is to enhance aspect-oriented business Process management with event-driven capabilities for discovering situations requiring Adaptations. To this end, we develop an aspect-oriented extension to BPMN2.0 and we couple it with an event-driven approach for detecting and reasoning about situations that require Adaptation of business Processes. We use event Processing in order to monitor the Process execution environment and, when execution violates some quality “threshold” or a problem arises, to detect it and trigger lookup for a suitable Process Adaptation, using a reasoning mechanism. We demonstrate that our approach is able to address simultaneously Adaptation on Process model and execution level.
Ioannis Patiniotakis - One of the best experts on this subject based on the ideXlab platform.
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Assessing Flexibility in Event-Driven Process Adaptation
Information Systems, 2019Co-Authors: Ioannis Patiniotakis, Dimitris Apostolou, Yiannis Verginadis, Nikos Papageorgiou, Gregoris MentzasAbstract:Abstract Business Process management (BPM) has emerged as a prominent information management approach focusing on the design, execution and governance of organizational business Processes. The ability to deal with both foreseen and unforeseen changes in business Processes is considered critical for contemporary business Process management systems. This paper proposes an approach that couples an event-driven framework for detecting and reasoning in situations that pose the need for Process Adaptations with MCDM methods for selecting Adaptations. The proposed approach has been implemented in an aspect-oriented extension of a BPMN2.0 engine in order to enact Adaptations of business Processes in real-time.
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Business Process Management Workshops - An Aspect Oriented Approach for Implementing Situational Driven Adaptation of BPMN2.0 Workflows
Business Process Management Workshops, 2013Co-Authors: Ioannis Patiniotakis, Dimitris Apostolou, Yiannis Verginadis, Nikos Papageorgiou, Gregoris MentzasAbstract:To address the issue of business Process Adaptation, we focus on handling Adaptation needs as cross-cutting concerns because they rely or must affect many parts of a business Process. Our research objective is to enhance aspect-oriented business Process management with event-driven capabilities for discovering situations requiring Adaptations. To this end, we develop an aspect-oriented extension to BPMN2.0 and we couple it with an event-driven approach for detecting and reasoning about situations that require Adaptation of business Processes. We use event Processing in order to monitor the Process execution environment and, when execution violates some quality “threshold” or a problem arises, to detect it and trigger lookup for a suitable Process Adaptation, using a reasoning mechanism. We demonstrate that our approach is able to address simultaneously Adaptation on Process model and execution level.