On the Complexity of Temporal Controllabilities for Workflow Schemata

Recently, different kinds of "controllability" have been proposed for workflow schemata modeling real world processes made of tasks and coordination activities. Temporal controllability is the capability of executing a workflow for all possible durations of all tasks satisfying all temporal constraints. Three different types of controllability are possible -- strong controllability, history-dependent controllability, and weak controllability -- and a general exponential-time algorithm to determine the kind of controllability has been proposed. In this paper we analyze the computational complexity of the temporal controllability problem to verify the quality of proposed algorithms. We show that the weak controllability problem is \coNP-complete, while strong controllability problem is in \u3a3_2^P and it is coNP-hard. Regarding the history-dependent controllability problem, we are able to show that it is a PSPACE problem but further research is required to determine its hardness characterization

Sound-and-Complete Algorithms for Checking the Dynamic Controllability of Conditional Simple Temporal Networks with Uncertainty

A Conditional Simple Temporal Network with Uncertainty (CSTNU) is a data structure for representing and reasoning about time. CSTNUs incorporate observation time-points from Conditional Simple Temporal Networks (CSTNs) and contingent links from Simple Temporal Networks with Uncertainty (STNUs). A CSTNU is dynamically controllable (DC) if there exists a strategy for executing its time-points that guarantees the satisfaction of all relevant constraints no matter how the uncertainty associated with its observation time-points and contingent links is resolved in real time. This paper presents the first sound-and-complete DC-checking algorithms for CSTNUs that are based on the propagation of labeled constraints and demonstrates their practicality

Flexible temporal constraint management in modularized processes

Managing temporal process constraints in modularized processes is an important task, both during the design, as it allows the reuse of temporal (child) process models, and during the checking of temporal properties of processes, as it avoids the necessity of ‘‘unfolding’’ child processes within the main process model. Taking into account the capability of providing modular solutions, modeling and checking temporal features of processes is still an open problem in the context of process-aware information systems. In this paper, we present and discuss a novel approach to represent flexible temporal constraints in modularized time-aware BPMN process models. To support temporal flexibility, allowed task durations are represented through guarded ranges that allow a limited (guarded) restriction of task durations during process execution if it is necessary to guarantee the satisfaction of all temporal constraints. We, then, propose how to derive a compact representation of the overall temporal behavior of such time-aware BPMN models. Such compact representation of child processes allows us to check the dynamic controllability (DC) of a parent timeaware process model without ‘‘unfolding’’ the child process models. Dynamic controllability guarantees that process models can have process instances (i.e., executions) satisfying all the temporal constraints for any possible combination of allowed durations of tasks and child processes. Possible approaches for even more flexibility by solving some kinds of DC violations are then introduced. We use a real process model from a healthcare domain as a motivating example, and we also present a proof-of-concept prototype confirming the concrete applicability of the solutions we propose, followed by an experimental evaluation

Dynamic Controllability Checking for Conditional Simple Temporal Networks with Uncertainty: New Sound-and-Complete Algorithms based on Constraint Propagation

A Conditional Simple Temporal Network with Uncertainty (CSTNU) is a data structure for representing and reasoning about time. CSTNUs incorporate "observation time-points" from Conditional Simple Temporal Networks (CSTNs) and "contingent links" from Simple Temporal Networks with Uncertainty (STNUs). A CSTNU is "dynamically controllable" (DC) if there exists a strategy for executing its time-points that guarantees the satisfaction of all relevant constraints no matter how the uncertainty associated with its observation time-points and contingent links is resolved in real time. This paper presents the first sound-and-complete DC-checking algorithms for CSTNUs based on the propagation of labeled constraints and demonstrates their practicality

Controlling Time-Awareness in Modularized Processes (Extended Version)

The proper handling of temporal process constraints is crucial in many application domains. However, a sophisticated support of time-aware processes is still missing in contemporary information systems. As a particular challenge, temporal constraints must be also handled for modularized processes (i.e., processes comprising subprocesses), enabling the re-use of process knowledge as well as the modular design of complex processes. This paper focuses on the representation and support of time-aware modularized processes. In particular, we present a sound and complete method to derive the duration restrictions of a time-aware (sub-)process in such a way that its temporal properties are completely specified. We then show how this characterization of a process can be utilized when re-using it as a subprocess within a modularized process

Managing time-awareness in modularized processes

Managing temporal process constraints in a suitable way is crucial for long-running business processes in many application domains. However, proper support of time-aware processes is still missing in contemporary information systems. This paper tackles a particular challenge existing in this context, namely the handling of temporal constraints for modularized processes (i.e., processes comprising subprocesses), which shall enable both the reuse of process knowledge and the modular design of complex processes. In detail, this paper focuses on the representation and support of time-aware modularized processes in process-aware information systems. To this end, we present a sound and complete method to derive the duration restrictions of a time-aware (sub-)process in such a way that its temporal properties are completely speci\ufb01ed. We then show how this characterization of a process can be utilized when reusing it as a subprocess within a modularized process. As a motivating example, we consider a compound process from healthcare. Altogether the proper handling of temporal constraints for modularized processes is crucial for the enhancement of time- and process-aware information systems

A modular approach to the specification and management of time duration constraints in BPMN

The modeling and management of business processes deals with temporal aspects both in the inherent representation of activity coordination and in the specification of activity properties and constraints. In this paper, we address the modeling and specification of constraints related to the duration of process activities. In detail, we consider the Business Process Model and Notation (BPMN) standard and propose an approach to define re-usable duration-aware process models that make use of existing BPMN elements for representing different nuances of activity duration at design time. Moreover, we show how advanced event-handling techniques may be exploited for detecting the violation of duration constraints during the process run-time. The set of process models specified in this paper suitably captures duration constraints at different levels of abstraction, by allowing designers to specify the duration of atomic tasks and of selected process regions in a way that is conceptually and semantically BPMN-compliant. Without loss of generality, we refer to real-world clinical working environments to exemplify our approach, as their intrinsic complexity makes them a particularly challenging and rewarding application environment