Dealing with Logical Failures for Collaborating Workflows

Logical failures occurring during workflow execution require the dynamic adaptation of affected workflows. The consequences such a dynamic adaptation may have for collaborating workflows have not yet been investigated sufficiently. We propose a rule-based approach for dynamic workflow adaptation to deal with logical failures. In our approach, workflow collaboration is based on agreements specifying the delivery time and quality of objects a workflow expects from its collaboration partners. Our mechanisms decide which collaborating workflows have to be informed when a dynamic adaptation is performed. In particular, we estimate the temporal and qualitative implications a dynamic adaptation has for collaboration partners. Because of the automated handling of logical failures, we expect that our approach significantly improves the robustness and correctness of collaborating workflows. The approach has been developed in the context of collaborative workflow-based care for cancer patients

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

Enabling Process Support for Advanced Applications with the AristaFlow BPM Suite

A process-aware information system (PAIS) will be not accepted by end users if its software clients do not support their native workflows or are too complex for them. When implementing business processes based on process management technology important issues are, therefore, how end-users can participate in the execution of the processes and how this can be accomplished as intuitively as possible. This becomes extremely important if high flexibility demands need to be fullled during process execution, while PAIS robustness and error safety need to be assured. In this software demonstration we show how the AristaFlow BPM Suite - an adaptive process management system developed by us - was applied to challenging applications in domains like healthcare, logistics, disaster management, and software development. The implementation of adaptive software clients in these different applications particularly proves the benefits provided by an open application programming interface (API) as offered by AristaFlow

ADEPT Workflow Management System Flexible Support for Enterprise-Wide Business Processes - Tool Presentation -

In this tool presentation we give an overview of the ADEPT workflow management system (WfMS), which is one of the few available research prototypes dealingwith enterprise-wide, adaptive workflow (WF) management. ADEPT offers sophisticated modeling concepts and advanced features, like temporal constraint management, ad-hoc WF changes, WF schema evolution, synchronization of inter-workflow dependencies, and scalability. We sketch these features and describe how they have been realized within ADEPT. In addition, we show which tools and interfaces are offered to developers and users in this context. ADEPT follows a holistic approach, i.e., the described concepts have not been implemented in an isolated fashion only, but are treated in conjunction with each other by integrating them within one WfMS

Robust and Flexible Error Handling in the AristaFlow BPM Suite

Process-aware information systems will be not accepted by users if rigidity or idleness due to failures comes with them. When implementing business processes based on process management technology one fundamental goal is to ensure robustness of the resulting process-aware information system. Meeting this goal becomes extremely complicated if high flexibility demands need to be fullled. This paper shows how the AristaFlow BPM Suite assists process participants in coping with errors and exceptional situations in a flexible and robust way. In particular, we focus on novel error handling procedures and capabilities using the flexibility provided by ad-hoc changes not shown in other context so far

An Approach for Supporting Ad-hoc Modifications in Distributed Workflow Management Systems

Supporting enterprise-wide or even cross-organizational business processes is a characteristic challenge for any workflow management system (WfMS). Scalability at the presence of high loads as well as the capability to dynamically modify running workflow (WF) instances (e.g., to cope with exceptional situations) are essential requirements in this context. Should the latter one, in particular, not be met, the WfMS will not have the necessary flexibility to cover the wide range of process-oriented applications deployed in many organizations. Scalability and flexibility have, for the most part, been treated separately in the relevant literature thus far. Even though they are basic needs for a WfMS, the requirements related with them are totally different. To achieve satisfactory scalability, on the one hand, the system needs to be designed such that a workflow instance can be controlled by several WF servers that are as independent from each other as possible. Yet dynamic WF modifications, on the other hand, necessitate a (logical) central control instance which knows the current and global state of a WF instance. For the first time, this paper presents methods which allow ad-hoc modifications (e.g., to insert, delete, or shift steps) to be performed in a distributed WfMS; i.e., in a WfMS with partitioned WF execution graphs and distributed WF control. It is especially noteworthy that the system succeeds in realizing the full functionality as given in the central case while, at the same time, achieving extremely favorable behavior with respect to communication costs

Schemaevolution in Workflow-Management-Systemen

Ein Schema (Muster, Entwurf) dient der modellhaften Beschreibung realer Sachverhalte. Mit Hilfe solcher Modelle kann der Mensch in seiner täglichen Arbeit unterstützt werden. So gibt es z. B. Datenbankschemata zur Beschreibung von Daten und deren Beziehung untereinander und Workflow-Schemata zur Modellierung von Arbeitsprozessen (engl.workflow)

Event-Oriented Dynamic Adaptation of Workflows: Model, Architecture and Implementation

Workflow management is widely accepted as a core technology to support long-term business processes in heterogeneous and distributed environments. However, conventional workflow management systems do not provide sufficient flexibility support to cope with the broad range of failure situations that may occur during workflow execution. In particular, most systems do not allow to dynamically adapt a workflow due to a failure situation, e.g., to dynamically drop or insert execution steps. As a contribution to overcome these limitations, this dissertation introduces the agent-based workflow management system AgentWork. AgentWork supports the definition, the execution and, as its main contribution, the event-oriented and semi-automated dynamic adaptation of workflows. Two strategies for automatic workflow adaptation are provided. Predictive adaptation adapts workflow parts affected by a failure in advance (predictively), typically as soon as the failure is detected. This is advantageous in many situations and gives enough time to meet organizational constraints for adapted workflow parts. Reactive adaptation is typically performed when predictive adaptation is not possible. In this case, adaptation is performed when the affected workflow part is to be executed, e.g., before an activity is executed it is checked whether it is subject to a workflow adaptation such as dropping, postponement or replacement. In particular, the following contributions are provided by AgentWork: A Formal Model for Workflow Definition, Execution, and Estimation: In this context, AgentWork first provides an object-oriented workflow definition language. This language allows for the definition of a workflow\u92s control and data flow. Furthermore, a workflow\u92s cooperation with other workflows or workflow systems can be specified. Second, AgentWork provides a precise workflow execution model. This is necessary, as a running workflow usually is a complex collection of concurrent activities and data flow processes, and as failure situations and dynamic adaptations affect running workflows. Furthermore, mechanisms for the estimation of a workflow\u92s future execution behavior are provided. These mechanisms are of particular importance for predictive adaptation. Mechanisms for Determining and Processing Failure Events and Failure Actions: AgentWork provides mechanisms to decide whether an event constitutes a failure situation and what has to be done to cope with this failure. This is formally achieved by evaluating event-condition-action rules where the event-condition part describes under which condition an event has to be viewed as a failure event. The action part represents the necessary actions needed to cope with the failure. To support the temporal dimension of events and actions, this dissertation provides a novel event-condition-action model based on a temporal object-oriented logic. Mechanisms for the Adaptation of Affected Workflows: In case of failure situations it has to be decided how an affected workflow has to be dynamically adapted on the node and edge level. AgentWork provides a novel approach that combines the two principal strategies reactive adaptation and predictive adaptation. Depending on the context of the failure, the appropriate strategy is selected. Furthermore, control flow adaptation operators are provided which translate failure actions into structural control flow adaptations. Data flow operators adapt the data flow after a control flow adaptation, if necessary. Mechanisms for the Handling of Inter-Workflow Implications of Failure Situations: AgentWork provides novel mechanisms to decide whether a failure situation occurring to a workflow affects other workflows that communicate and cooperate with this workflow. In particular, AgentWork derives the temporal implications of a dynamic adaptation by estimating the duration that will be needed to process the changed workflow definition (in comparison with the original definition). Furthermore, qualitative implications of the dynamic change are determined. For this purpose, so-called quality measuring objects are introduced. All mechanisms provided by AgentWork include that users may interact during the failure handling process. In particular, the user has the possibility to reject or modify suggested workflow adaptations. A Prototypical Implementation: Finally, a prototypical Corba-based implementation of AgentWork is described. This implementation supports the integration of AgentWork into the distributed and heterogeneous environments of real-world organizations such as hospitals or insurance business enterprises

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Capitalization and sharing of lessons learned play an essential role in managing the activities of industrial systems. This is particularly the case for the maintenance management, especially for distributed systems often associated with collaborative decision-making systems. Our contribution focuses on the formalization of the expert knowledge required for maintenance actors that will easily engage support tools to accomplish their missions in collaborative frameworks. To do this, we use the conceptual graphs formalism with their reasoning operations for the comparison and integration of several conceptual graph rules corresponding to different viewpoint of experts. The proposed approach is applied to a case study focusing on the maintenance management of a rotary machinery system