Weak, Strong and Dynamic Controllability of Access-Controlled Workflows Under Conditional Uncertainty

A workflow (WF) is a formal description of a business process in which single atomic work units (tasks), organized in a partial order, are assigned to processing entities (agents) in order to achieve some business goal(s). A workflow management system must coordinate the execution of tasks and WF instances. Usually, the assignment of tasks to agents is accomplished by external constraints not represented in a WF. An access-controlled workflow (ACWF) extends a classical WF by explicitly representing agent availability for each task and authorization constraint. Authorization constraints model which users are authorized for which tasks depending on \u201cwho did what\u201d. Recent research has addressed temporal controllability of WFs under conditional and temporal uncertainty. However, controllability analysis for ACWFs under conditional uncertainty has never been addressed before. In this paper, we define weak, strong and dynamic controllability of ACWFs under conditional uncertainty, we present algorithmic approaches to address each of these types of controllability, and we synthesize execution strategies that specify which user has been (or will be) assigned to which task

Non-Local Configuration of Component Interfaces by Constraint Satisfaction

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s10601-020-09309-y.Service-oriented computing is the paradigm that utilises services as fundamental elements for developing applications. Service composition, where data consistency becomes especially important, is still a key challenge for service-oriented computing. We maintain that there is one aspect of Web service communication on the data conformance side that has so far escaped the researchers attention. Aggregation of networked services gives rise to long pipelines, or quasi-pipeline structures, where there is a profitable form of inheritance called flow inheritance. In its presence, interface reconciliation ceases to be a local procedure, and hence it requires distributed constraint satisfaction of a special kind. We propose a constraint language for this, and present a solver which implements it. In addition, our approach provides a binding between the language and C++, whereby the assignment to the variables found by the solver is automatically translated into a transformation of C++ code. This makes the C++ Web service context compliant without any further communication. Besides, it uniquely permits a very high degree of flexibility of a C++ coded Web service without making public any part of its source code.Peer reviewe

NightSplitter: a scheduling tool to optimize (sub)group activities

International audienceHumans are social animals and usually organize activities in groups. However, they are often willing to split temporarily a bigger group in subgroups to enhance their preferences. In this work we present NightSplitter, an on-line tool that is able to plan movie and dinner activities for a group of users, possibly splitting them in subgroups to optimally satisfy their preferences. We first model and prove that this problem is NP-complete. We then use Constraint Programming (CP) or alternatively Simulated Annealing (SA) to solve it. Empirical results show the feasibility of the approach even for big cities where hundreds of users can select among hundreds of movies and thousand of restaurants

Portfolio Approaches for Constraint Optimization Problems

International audienceWithin the Constraints Satisfiability Problems (CSP) context, a methodology that has proved to be particularly performant consists in using a portfolio of different constraint solvers. Nevertheless, comparatively few studies and investigations has been done in the world of Constraint Optimization Problems (COP). In this work, we provide a generalization to COP as well as an empirical evaluation of different state of the art existing CSP portfolio approaches properly adapted to deal with COP. Experimental results confirm the effectiveness of portfolios even in the optimization field, and could give rise to some interesting future research

Lightweight MAC algorithms

//csweb.ucc.ie/˜dongen/papers/4C/03/4C-02-2003.pdf Arc-consistency algorithms are the workhorse of backtrackers that Maintain Arc-Consistency (MAC). This report will provide experimental evidence that, despite common belief to the contrary, it is not always necessary for a good arc-consistency algorithm to have an optimal worst case time-complexity. To sacrifice this optimality allows MAC solvers that (1) do not need additional data structures during search, (2) have an excellent average time-complexity, and (3) have a space-complexity which improves significantly on that of MAC solvers that have optimal arc-consistency components. Results will be presented from an experimental comparison between MAC-2001, MAC-3d and related algorithms. MAC-2001 has an arc-consistency component with an optimal worst case time-complexity, whereas MAC-3d does not. MAC-2001 requires additional data structures during search, whereas MAC-3d does not. MAC-3d has a space-complexity of O(e + nd), where n is the number of variables, d the maximum domain size, and e the number of constraints. We shall demonstrate that MAC-2001’s space-complexity is O(ed min(n, d)). MAC-2001 required about 35 % more solution time on average than MAC-3