Simulation is critical when studying real operational behavior of increasingly complex Cyber-Physical Systems, forecasting future behavior, and experimenting with hypothetical scenarios. A critical aspect of simulation is the ability to evaluate large-scale systems within a reasonable time frame while modeling complex interactions between millions of components. However, modern simulations face limitations in provisioning this functionality for CPSs in terms of balancing simulation complexity with performance, resulting in substantial operational costs required for completing simulation execution. Moreover, users are required to have expertise in modeling and configuring simulations to infrastructure which is time consuming. In this paper we present Simulation EnvironmEnt Distributor (SEED), a novel approach for simulating large-scale CPSs across a loosely-coupled distributed system requiring minimal user configuration. This is achieved through automated simulation partitioning and instantiation while enforcing tight event messaging across the system. SEED operates efficiently within both small and large-scale OTS hardware, agnostic of cluster heterogeneity and OS running, and is capable of simulating the full system and network stack of a CPS. Our approach is validated through experiments conducted in a cluster to simulate CPS operation. Results demonstrate that SEED is capable of simulating CPSs containing 2,000,000 tasks across 2,000 nodes with only 6.89× slow down relative to real time, and executes effectively across distributed infrastructure.

The ability to reliably distribute simulations across a distributed system and seamlessly integrate them as a workflow regardless of their level of abstraction is critical to improving the quality of product manufacturing. This paper presents the DIVIDER architecture for managing and maintaining real-time performance simulations integrated through SOAs. The described approach captures features present in complex workflow patterns such as asynchronous arbitrary cycles and estimates the worst case execution time in the context of the interfering execution environment.

A major application area in the computer vision domain is gesture recognition, requiring real-time image classification to respond to human interactions. However, current state-of-the-art high-quality algorithms for image classification do not meet many dynamic real-time requirements. This paper presents the development of M-VCR - a novel approach for improving the reliability of real-time image classification. M-VCR increases the quality of classifications under real-time constraints through the adoption of fast classification algorithms, although these algorithms individually produce lower quality results, utilisation under a 'consensus' approach can achieve results equivalent to those of much higher-quality algorithms. The proposed approach also allows for different algorithms to be utilised in parallel, building on the fault tolerance technique of N-versioning. A significant improvement in image classification is experimentally demonstrated for both the SURF and MSER feature detectors through our integration consensus approach. This improvement is delivered entirely through the integration method without requiring modification of the source algorithms being used.

As the automotive industry moves towards reduced physical prototyping it is becoming more dependent on distributed simulations. However, the current technologies do not fully enable real-time distributed simulations which involve both virtual and physical components. This paper considers the current approaches to real-time distributed simulation and proposes the use of service-orientation. The highlights and current shortfalls of current research in real-time service orientation are then identified. Finally a key area of research is focused upon requiring a fundamental change of the understanding of quality of service and capability that is necessary to enable dependable real-time service orientated architectures.

This paper presents the development of REF-WS an approach to enable a Web Service provider to reliably evolve their service through the application of refactoring transformations. REF-WS is intended to aid service providers, particularly in a reliability and performance constrained domain as it permits upgraded 'non-backwards compatible' services to be deployed into a performance constrained network where existing consumers depend on an older version of the service interface. In order for this to be successful, the refactoring and message mediation needs to occur without affecting functional compatibility with the services' consumers, and must operate within the performance overhead expected of the original service, introducing as little latency as possible. Furthermore, compared to a manually programmed solution, the presented approach enables the service developer to apply and parameterize refactorings with a level of confidence that they will not produce an invalid or 'corrupt' transformation of messages. This is achieved through the use of preconditions for the defined refactorings.

Sensor networks have the potential to revolutionise the capture, processing and communication of critical data for use of disaster rescue and relief. In order to provide a dependable rescue capability through dynamically integrating newly developed and legacy sensor systems with other systems and computing, new methodologies are required for the dependable integration of services in heterogeneous environments. In this study, the authors present a new architectural model which can proactively self-adapt to changes and evolution occurring in the provision of search and rescue capabilities in a dynamic environment. This performance and reliability of the approach has been evaluated using simulations in a dynamic environment and demonstrated through developing and testing a demonstration system for a scenario of disaster area monitoring.

The vision of service-oriented computing is one of loosely coupled services that create agile applications to encapsulate business objectives and processes. The potential of services to form complex systems of systems, with emergent behaviour, necessitates the need to understand how we can we develop sufficient confidence in their qualities. In this paper we argue that successful development and evolution of service oriented computing is dependent on making informed decisions at the architectural level. This poses a number of challenges concerning how to evaluate such system architectures and the measurements and metrics that are important in their assessment. This paper describes research-in-progress into the development of a scenario-based architectural evaluation framework that allows architectural-level reasoning across systems of systems in the context of Network Enabled Capability: a UK Ministry endeavour designed to achieve enhanced [military] effect through the physical networking and coherent integration of existing and future resources.

One of the key concerns in the conceptualisation of a single object is understanding the context under which that object exists (or can exist). This contextual understanding should provide us with clear conceptual identification of an object including implicit situational information and detail of surrounding objects. For example in learning terms, a learner should be aware of concepts related to the context of their field of study and a surrounding cloud of contextually related concepts. This paper explores the use of an evolving community maintained knowledge-base (that of Wikipedia) in order to prioritise concepts that are semantically relevant to the user's interest space.

Network enabled capability (NEC) is the U.K. Ministry of Defencepsilas response to the quickly changing conflict environment in which its forces must operate. In NEC, systems need to be integrated in context, to assist in human activity and provide dependable inter-operation. In order to provide reliable and sustainable military capability, fast paced changes must be conducted without halting the operation of a capability. In this paper we present the concept of evolutionary service-oriented architecture for delivering sustainable capability. The reliability of the architecture is evaluated by simulations using a computer-based model. The simulation results indicate that the evolutionary service-oriented architecture can provide higher reliability and sustainability in the provision of capability in a dynamic environment.

The concept of a scenario has long been utilized in military procurement as a means of evaluating capability in an operational context. With the advent of initiatives such as the USA Department of Defence's Network-Centric Operations and the UK Ministry of Defence's Network Enabled Capability, research into the application of service-oriented architectures (SOA) as a means of delivering capability is being undertaken. A promising output of this research is the definition of scenario based evaluation models that can be applied to SOA. This paper examines the application of a military scenario framework to more conventional software evaluation situations by means of case studies. This demonstrates that similar techniques can be used in their construction and thus provides a basis for the application of scenario based evaluation models in future research.

How can we solve the problem of information overload in news syndication? This poster outlines the path from keyword-based body text matching to distance-measurable taxonomic tag matching, on to context scale and practical uses.

Six years after Tim Berners-Lee and his colleagues drew the vision of the Semantic Web (SW) in 1998, the SW is very likely to take off in the near future based on a set of specifications such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL). As a natural result, people will see the coexistence of the WWW and the SW for a certain long time. Under this situation, how to bridge the gap between the WWW and the SW will become an inevitable issue. In this paper, we present a context-aware approach on enabling agents to understand semantic resources on the two webs. The basic idea of this approach is to structure user-centred contextual information to facilitate agent-based (inter)operations on the network. Based on this idea, we design a Knowledge Interoperation Reference Model (KIRM) to address the interoperation issue at the global level. To demonstrate how agents understand semantic resources in a context-aware manner in real practices, we develop a news aggregation system based on RDF Site Summary / Really Simple Syndication (RSS) using agents. Considering the fact that RSS format set is a combination of XML and RDF, the success of agent understanding of RSS content under specific semantic contexts shows the possibility of extending and applying the context-aware approach in other semantic-based applications on both the WWW and the SW in the future.