Prescriptive Semantics For Big-Step Modelling Languages

With the popularity of model-driven methodologies and the abundance of modelling languages, a major question for a modeller is: Which language is suitable for modelling a system under study? To answer this question, one not only needs to know the range of relevant languages for modelling the system under study, but also needs to be able to compare these languages. In this dissertation, I consider these challenges from a semantic point of view for a diverse range of behavioural modelling languages that I refer to as the family of Big-Step Modelling Languages (BSMLs). There is a plethora of BSMLs, including statecharts, its variants, SCR, un-clocked variants of synchronous languages (e.g., Esterel and Argos), and reactive modules. BSMLs are often used to model systems that continuously interact with their environments. In a BSML model, the reaction of the model to an environmental input is a big step, which consists of a sequence of small steps, each of which can be the concurrent execution of a set of transitions. To provide a systematic method to understand and compare the semantics of BSMLs, this dissertation introduces the big-step semantic deconstruction framework that deconstructs the semantic design space of BSMLs into eight high-level, independent semantic aspects together with the enumeration of the common semantic options of each semantic aspect. The dissertation also presents a comparative analysis of the semantic options of each semantic aspect to assist one to choose one semantic option over another. A key idea in the big-step semantic deconstruction is that the high-level semantic aspects in the deconstruction recognize a big step as a whole, rather than only considering its constituent transitions operationally. A novelty of the big-step semantic deconstruction is that it lends itself to a systematic semantic formalization of most of the languages in the deconstruction. The dissertation presents a parametric, formal semantic definition method whose parameters correspond to the semantic aspects of the deconstruction, and thus it produces prescriptive semantics: The manifestation of a semantic option in the semantics of a BSML can be clearly identified. The way transitions are ordered to form a big step in a BSML is a source of semantic complexity: A modeller needs to be aware of the possible orders of the execution of transitions when constructing and analyzing a model. The dissertation introduces three semantic quality attributes that each exempts a modeller from considering an aspect of ordering in big steps. The ranges of BSMLs that support each of these semantic quality attributes are formally specified. These specifications indicate that achieving a semantic quality attribute in a BSML is a cross-cutting concern over the choices of its different semantic options. The semantic quality attributes together with the semantic analysis of individual semantic options can be used in tandem to assist a modeller or a semanticist to compare two BSMLs or to create a new, desired BSML from scratch. Through the big-step semantic deconstruction, I have discovered that some of the semantic aspects of BSMLs can be uniformly described as forms of synchronization. The dissertation presents a general synchronization framework for behavioural modelling languages. This framework is based on a notion of synchronization between transitions of complementary roles. It is parameterized by the number of interactions a transition can take part in, i.e., one vs. many, and the arity of the interaction mechanisms, i.e., exclusive vs. shared, which are considered for the complementary roles to result in 16 synchronization types. To enhance BSMLs with the capability to use the synchronization types, a synchronizer syntax is introduced for BSMLs, resulting in the family of Synchronizing Big-Step Modelling Languages (SBSMLs). Using the expressiveness of SBSMLs, the dissertation describes how underlying the semantics of many modelling constructs, such as multi-source, multi-destination transitions, various composition operators, and workflow patterns, there is a notion of synchronization that can be systematically modelled in SBSMLs

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Special Session on Industry 4.0

No abstract available

Non-functional Property based service selection: A survey and classification of approaches

In recent years there has been much effort dedicated to developing approaches for service selection based on non-functional properties. It is clear that much progress has been made, and by considering the individual approaches there is some overlap in functionality, but obviously also some divergence. In this paper we contribute a classification of approaches, that is, we define a number of criteria which allow to differentiate approaches. We use this classification to provide a comparison of existing approaches and in that sense provide a survey of the state of the art of the field. Finally we make some suggestions as to where the research in this area might be heading and which new challenges need to be addressed

A characteristics framework for Semantic Information Systems Standards

Semantic Information Systems (IS) Standards play a critical role in the development of the networked economy. While their importance is undoubted by all stakeholders—such as businesses, policy makers, researchers, developers—the current state of research leaves a number of questions unaddressed. Terminological confusion exists around the notions of “business semantics”, “business-to-business interoperability”, and “interoperability standards” amongst others. And, moreover, a comprehensive understanding about the characteristics of Semantic IS Standards is missing. The paper addresses this gap in literature by developing a characteristics framework for Semantic IS Standards. Two case studies are used to check the applicability of the framework in a “real-life” context. The framework lays the foundation for future research in an important field of the IS discipline and supports practitioners in their efforts to analyze, compare, and evaluate Semantic IS Standard

Towards Analytics Aware Ontology Based Access to Static and Streaming Data (Extended Version)

Real-time analytics that requires integration and aggregation of heterogeneous and distributed streaming and static data is a typical task in many industrial scenarios such as diagnostics of turbines in Siemens. OBDA approach has a great potential to facilitate such tasks; however, it has a number of limitations in dealing with analytics that restrict its use in important industrial applications. Based on our experience with Siemens, we argue that in order to overcome those limitations OBDA should be extended and become analytics, source, and cost aware. In this work we propose such an extension. In particular, we propose an ontology, mapping, and query language for OBDA, where aggregate and other analytical functions are first class citizens. Moreover, we develop query optimisation techniques that allow to efficiently process analytical tasks over static and streaming data. We implement our approach in a system and evaluate our system with Siemens turbine data

Developing domain ontologies for course content

Ontologies have the potential to play an important role in instructional design and the development of course content. They can be used to represent knowledge about content, supporting instructors in creating content or learners in accessing content in a knowledge-guided way. While ontologies exist for many subject domains, their quality and suitability for the educational context might be unclear. For numerous subjects, ontologies do not exist. We present a method for domain experts rather than ontology engineers to develop ontologies for use in the delivery of courseware content. We will focus in particular on relationship types that allow us to model rich domains adequately