Automatic service categorisation through machine learning in emergent middleware

The modern environment of mobile, pervasive, evolving services presents a great challenge to traditional solutions for enabling interoperability. Automated solutions appear to be the only way to achieve interoperability with the needed level of flexibility and scalability. While necessary, the techniques used to determine compatibility, as a precursor to interaction, come at a substantial computational cost, especially when checks are performed between systems in unrelated domains. To overcome this, we apply machine learning to extract high-level functionality information through text categorisation of a system's interface description. This categorisation allows us to restrict the scope of compatibility checks, giving an overall performance gain when conducting matchmaking between systems. We have evaluated our approach on a corpus of web service descriptions, where even with moderate categorisation accuracy, a substantial performance benefit can be found. This in turn improves the applicability of our overall approach for achieving interoperability in the Connect project

Mediating Connector Patterns for Components Interoperability

International audienceA key objective for ubiquitous environments is to enable system interoperability between system's components that are highly heterogeneous. In particular, the challenge is to embed in the system architecture the necessary support to cope with behavioral diversity in order to allow components to coordinate and communicate. In this paper we present the design building blocks for the dynamic and on-the-fly interoperability between heterogeneous components. Specifically, we describe an Architectural Pattern called Mediating Connector, that is the key enabler for communication. In addition, we present a set of Basic Mediator Patterns, that describe the basic mismatches which can occur when components try to interact, and their corresponding solution

Application-Layer Connector Synthesis

International audienceThe heterogeneity characterizing the systems populating the Ubiquitous Computing environment prevents their seamless interoperability. Heterogeneous protocols may be willing to cooperate in order to reach some common goal even though they meet dynamically and do not have a priori knowledge of each other. Despite numerous e orts have been done in the literature, the automated and run-time interoperability is still an open challenge for such environment. We consider interoperability as the ability for two Networked Systems (NSs) to communicate and correctly coordinate to achieve their goal(s). In this chapter we report the main outcomes of our past and recent research on automatically achieving protocol interoperability via connector synthesis. We consider application-layer connectors by referring to two conceptually distinct notions of connector: coordinator and mediator. The former is used when the NSs to be connected are already able to communicate but they need to be speci cally coordinated in order to reach their goal(s). The latter goes a step forward representing a solution for both achieving correct coordination and enabling communication between highly heterogeneous NSs. In the past, most of the works in the literature described e orts to the automatic synthesis of coordinators while, in recent years the focus moved also to the automatic synthesis of mediators. Within the Connect project, by considering our past experience on automatic coordinator synthesis as a baseline, we propose a formal theory of mediators and a related method for automatically eliciting a way for the protocols to interoperate. The solution we propose is the automated synthesis of emerging mediating connectors (i.e., mediators for short)

A Theory of Mediators for Eternal Connectors

International audienceOn the fly synthesis of mediators is a revolutionary approach to the seamless networking of today's and future digital systems that increasingly need be connected. The resulting emergent mediators (or Connectors) adapt the interaction protocols run by the connected systems to let them communicate. However, although the mediator concept has been studied and used quite extensively to cope with many heterogeneity dimensions, a remaining key challenge is to support on-the-fly synthesis of mediators. Towards this end, this paper introduces a theory of mediators for the ubiquitous networking environment. The proposed formal model: (i) precisely characterizes the problem of interoperability between networked systems, and (ii) paves the way for automated reasoning about protocol matching (interoperability) and related mediator synthesis

Discovering pattern-based mediator services from communication logs

Process discovery is a technique for deriving a conceptual high-level process model from the execution logs of a running implementation. The technique is particularly useful when no high-level model is available or in case of significant gaps between process documentation and implementation. The discovered model makes the implementation accessible to various kinds of analysis for functional and non-functional properties. In this paper we extend process discovery to mediator services (or adapters) which adapt the messaging protocols of 2 or more otherwise incompatible services. We propose a technique that takes as input logs of communication behaviors—one log for each service connected to the adapter—and a library of high-level data transformation rules relevant for the domain of the adapter, and then returns an operational adapter model describing the control-flow and the data flow of the adapter in terms of Coloured Petri Nets – if such model exists. We discuss benefits and limitations of this idea and evaluate it with a prototype implementation on industrial size models. Keywords: Process Mining; Service Mining; Pattern Based Design; Coloured Petri nets; synthesi

Detecting inconsistencies between process models and textual descriptions

Text-based and model-based process descriptions have their own particular strengths and, as such, appeal to different stakeholders. For this reason, it is not unusual to find within an organization descriptions of the same business processes in both modes. When considering that hundreds of such descriptions may be in use in a particular organization by dozens of people, using a variety of editors, there is a clear risk that such models become misaligned. To reduce the time and effort needed to repair such situations, this paper presents the first approach to automatically identify inconsistencies between a process model and a corresponding textual description. Our approach leverages natural language processing techniques to identify cases where the two process representations describe activities in different orders, as well as model activities that are missing from the textual description. A quantitative evaluation with 46 real-life model-text pairs demonstrates that our approach allows users to quickly and effectively identify those descriptions in a process repository that are inconsistent

Improving business processes : does anybody have an idea?

As part of process redesign initiatives, substantial time is spent on the systematic description and analysis of the as-is process. By contrast, to-be scenarios are often generated in a less rigorous way. Only one or a few workshops are organized for this purpose, which rely on the use of techniques that are susceptible to bias and incompleteness, e.g. brainstorming. In this paper, we evaluate a new technique for generating process improvement ideas: the RePro (Rethinking of Processes) technique. Its backbone is formed by process improvement principles that guide practitioners in a systematic and comprehensive exploration of the solution space. An experiment was conducted to compare the performance of the RePro technique with traditional brainstorming. Results confirm the potential for using a more advanced technique during process redesign workshops, but also show that the way such a technique is used strongly affects its performance. Keywords: Process redesign Process innovation Improvement principles Controlled experiment RePr

Avoiding over-fitting in ILP-based process discovery

The aim of process discovery is to discover a process model based on business process execution data, recorded in an event log. One of several existing process discovery techniques is the ILP-based process discovery algorithm. The algorithm is able to unravel complex process structures and provides formal guarantees w.r.t. the model discovered, e.g., the algorithm guarantees that a discovered model describes all behavior present in the event log. Unfortunately the algorithm is unable to cope with exceptional behavior present in event logs. As a result, the application of ILP-based process discovery techniques in everyday process discovery practice is limited. This paper addresses this problem by proposing a filtering technique tailored towards ILP-based process discovery. The technique helps to produce process models that are less over-fitting w.r.t. the event log, more understandable, and more adequate in capturing the dominant behavior present in the event log. The technique is implemented in the ProM framework. Keywords: Process mining Process discovery Integer linear programming Filterin