6,879 research outputs found

    Identifying and addressing adaptability and information system requirements for tactical management

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    Adaptive Process Management in Cyber-Physical Domains

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    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

    A planning approach to the automated synthesis of template-based process models

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    The design-time specification of flexible processes can be time-consuming and error-prone, due to the high number of tasks involved and their context-dependent nature. Such processes frequently suffer from potential interference among their constituents, since resources are usually shared by the process participants and it is difficult to foresee all the potential tasks interactions in advance. Concurrent tasks may not be independent from each other (e.g., they could operate on the same data at the same time), resulting in incorrect outcomes. To tackle these issues, we propose an approach for the automated synthesis of a library of template-based process models that achieve goals in dynamic and partially specified environments. The approach is based on a declarative problem definition and partial-order planning algorithms for template generation. The resulting templates guarantee sound concurrency in the execution of their activities and are reusable in a variety of partially specified contextual environments. As running example, a disaster response scenario is given. The approach is backed by a formal model and has been tested in experiment

    CAiSE Radar 2016

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    The CAiSE Radar is an experimental format, established for CAiSE 2016, to make CAiSE workshops livelier, exciting, stimulate discussions, and attract additional active participants by establishing an environment where not only well established and validated research is reported but research in infancy, new ideas, and potentially interesting research projects can be presented and discussed. So similarly to a radar, the idea is to enable researchers to look into the future of the field and identify upcoming trends early. The aim of such effort is on one hand to contribute to the building of research communities and promote the integration of young researchers into the community, and on the other hand to provide opportunities to discuss ideas early and to receive additional opinions on planned research

    Enabling Flexibility in Process-Aware Information Systems: Challenges, Methods, Technologies

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    In today’s dynamic business world, the success of a company increasingly depends on its ability to react to changes in its environment in a quick and flexible way. Companies have therefore identified process agility as a competitive advantage to address business trends like increasing product and service variability or faster time to market, and to ensure business IT alignment. Along this trend, a new generation of information systems has emerged—so-called process-aware information systems (PAIS), like workflow management systems, case handling tools, and service orchestration engines. With this book, Reichert and Weber address these flexibility needs and provide an overview of PAIS with a strong focus on methods and technologies fostering flexibility for all phases of the process lifecycle (i.e., modeling, configuration, execution and evolution). Their presentation is divided into six parts. Part I starts with an introduction of fundamental PAIS concepts and establishes the context of process flexibility in the light of practical scenarios. Part II focuses on flexibility support for pre-specified processes, the currently predominant paradigm in the field of business process management (BPM). Part III details flexibility support for loosely specified processes, which only partially specify the process model at build-time, while decisions regarding the exact specification of certain model parts are deferred to the run-time. Part IV deals with user- and data-driven processes, which aim at a tight integration of processes and data, and hence enable an increased flexibility compared to traditional PAIS. Part V introduces existing technologies and systems for the realization of a flexible PAIS. Finally, Part VI summarizes the main ideas of this book and gives an outlook on advanced flexibility issues. The attached pdf file gives a preview on Chapter 3 of the book which explains the book's overall structure

    Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

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    Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

    Supporting adaptiveness of cyber-physical processes through action-based formalisms

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    Cyber Physical Processes (CPPs) refer to a new generation of business processes enacted in many application environments (e.g., emergency management, smart manufacturing, etc.), in which the presence of Internet-of-Things devices and embedded ICT systems (e.g., smartphones, sensors, actuators) strongly influences the coordination of the real-world entities (e.g., humans, robots, etc.) inhabitating such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS, called SmartPM, which combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on three well-established action-based formalisms developed for reasoning about actions in Artificial Intelligence (AI), including the situation calculus, IndiGolog and automated planning. Interestingly, the use of SmartPM does not require any expertise of the internal working of the AI tools involved in the system

    Change Support in Process-Aware Information Systems - A Pattern-Based Analysis

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    In today's dynamic business world the economic success of an enterprise increasingly depends on its ability to react to changes in its environment in a quick and flexible way. Process-aware information systems (PAIS) offer promising perspectives in this respect and are increasingly employed for operationally supporting business processes. To provide effective business process support, flexible PAIS are needed which do not freeze existing business processes, but allow for loosely specified processes, which can be detailed during run-time. In addition, PAIS should enable authorized users to flexibly deviate from the predefined processes if required (e.g., by allowing them to dynamically add, delete, or move process activities) and to evolve business processes over time. At the same time PAIS must ensure consistency and robustness. The emergence of different process support paradigms and the lack of methods for comparing existing change approaches have made it difficult for PAIS engineers to choose the adequate technology. In this paper we suggest a set of changes patterns and change support features to foster the systematic comparison of existing process management technology with respect to process change support. Based on these change patterns and features, we provide a detailed analysis and evaluation of selected systems from both academia and industry. The identified change patterns and change support features facilitate the comparison of change support frameworks, and consequently will support PAIS engineers in selecting the right technology for realizing flexible PAIS. In addition, this work can be used as a reference for implementing more flexible PAIS
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