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This paper aims to demonstrate that a policy-based middleware solution which facilitates the development of context-aware applications and the integration of the heterogeneous devices should be provided for ubiquitous computing environments. Ubiquitous computing targets the provision of seamless services and applications by providing an environment that involves a variety of devices having different capabilities. These applications help transforming the physical spaces into computationally active and smart environments. The design of applications in these environments needs to consider the heterogeneous devices, applications preferences and rapidly changing contexts. The applications, therefore, need to be context-aware so that they can adapt to different situations in real-time.

In this paper, we argue that a policy-based middleware solution that facilitates the development of context-aware applications and the integration of the heterogeneous devices should be provided for ubiquitous computing environments. The middleware allows applications to track items and acquire contextual information about them easily, reason about this information captured using different logics and then adapt to changing contexts. A key issue in these environments is to allow heterogeneous applications to express their business rules once, and get the preferred data once they are captured by the middleware without any intervention from the application side.

Our middleware tackles this problem by using policies to define the different applications’ rules and preferences. These policies can specify rules about the middleware services to be used, type of data captured, devices used, user roles, context information and any other type of conditions.

In this paper, we propose the design of a flexible and performant ubiquitous computing, and context-aware middleware called FlexRFID along with its evaluation results.

A novel distributed middleware service platform, called MidGate platform, is presented in this paper. The central contribution is description of the developed MidGate platform and its architecture focusing especially on the adaptation, context‐awareness, and personalization of mobile and pervasive services. The research problem addressed is how to facilitate the development of interoperable applications and services into heterogeneous and distributed service gateway based environments. A requirement analysis of future mobile and pervasive services and key technologies has been carried out to establish a solid base and requirements for the development of the MidGate platform. The key mechanisms supporting adaptation, context‐awareness, and personalization of applications and services are presented. The novel middleware architecture solution of the MidGate platform utilizing these key mechanisms is also described. The MidGate architecture utilizes the emerging Generic Service Elements (GSE) approach, where generic and collectively utilizable services are provided to applications as middleware services that are part of a service platform. The main contribution of this research is the definition of a set of GSEs, the related MidGate platform architecture and its evaluation. The evaluation of the MidGate platform has been carried out in series of laboratory prototypes. The evaluation indicates that the MidGate platform solution is well applicable in various service gateway‐based distributed systems and extends well into resource‐constrained mobile environments.

Presence of innumerable sensors, complex deduction of contexts from sensor data, and reusability of contextual information impose the requirement of middleware for context aware computing. Smart applications, hosted in myriad devices (e.g. PDA, mobile, PCs), acquire different contexts from the middleware and act intelligently based on the available contexts in a context‐aware computing environment. As the system grows larger, scalable delivery of contexts from the middleware to numerous context‐aware applications will be inevitable. However, pure unicast based or pure broadcast‐based dissemination cannot provide high scalability as well as low‐average latency. The purpose of this paper is to present a scalable context delivery mechanism for the middlewares to facilitate the development of larger context‐aware computing systems.

The proposed scheme is based on hybrid data dissemination technique where the most frequently requested data (e.g. HOT contexts) are delivered through multicast and the rest (e.g. COLD contexts) are delivered through unicast to reduce network traffic. The paper dynamically prioritizes and classifies the HOT and COLD context data depending on the number of requests and longest waiting time. Moreover, the division of bandwidth between the delivery of HOT and COLD contexts reduces average latency. Polling traffic is decreased by incorporating leasing mechanism. Extensive simulation is conducted to evaluate the proposed scheme.

The mechanism dynamically prioritizes and classifies the hot and cold context data depending on the request rate and longest waiting time. The solution addresses the push popularity problem that occurs in the passive as the passive clients access data without sending explicit requests. The leasing mechanism is incorporated to reduce the periodical requests (polling) for better performance.

The paper is of value in presenting a scalable context delivery mechanism for the middlewares to facilitate the development of larger context‐aware computing systems and also in presenting implementation details of a prototype that is developed using Jini framework and Java reliable multicast service (JRMS) library.

Context‐aware mobile computing extends the horizons of the conventional computing model to a ubiquitous computing environment that serves users at anytime, anywhere. To achieve this, mobile applications need to adapt their behaviors to the changing context. The purpose of this paper is to present a generalized adaptive middleware infrastructure for context‐aware computing.

Owing to the vague nature of context and uncertainty in context aggregation for making adaptation decisions, the paper proposes a fuzzy‐based service adaptation model (FSAM) to improve the generality and effectiveness of service adaptation using fuzzy theory.

By the means of fuzzification of the context and measuring the fitness degree between the current context and the predefined optimal context, FSAM selects the most suitable policy to adopt for the most appropriate service. The paper evaluates the middleware together with the FSAM inference engine by using a Campus Assistant application.

The paper is of value in presenting a generalized adaptive middleware infrastructure for context‐aware computing and also comparing the performance of the fuzzy‐based solution with a conventional threshold‐based approach for context‐aware adaptation.

Context awareness is one of the key aspects of pervasive computing systems. In such systems, a plethora of dynamic context information needs to be constantly retrieved, soundly interpreted, rapidly processed, maintained in various repositories, and securely disseminated. Thus, a flexible, scalable and interoperable context representation scheme needs to be established and solid context management mechanisms need to be adopted, which will perform well in large‐scale distributed pervasive systems. This paper elaborates on the COMPACT context middleware that has been designed to cope with the issues above and saturate pervasive computing environments with context awareness functionality.

This paper aims to propose an approach for the self-adaptation of the Web composition called SAMIWA. The SAMIWA framework helps users during the search, invocation and composition of the appropriate Web service.

The authors’ approach allows expressing requirements by taking into account potential users’ context in addition to the functional one.

In this paper, the authors introduce a new context-aware approach that provides a dynamic adaptation of service compositions.

The author has implemented a Web application that enables selection and composition of the most appropriate composite service.

Context‐awareness is an essential property of any pervasive system perceiving its environment. Such a system captures and processes context, i.e. the features describing the relevant aspects of environment state and user behaviour. However, development of these systems still requires solving a number of research and engineering challenges. The purpose of this paper is to propose perception framework, a RESTful middleware which simplifies and accelerates the development of pervasive systems. Perception framework allows constructing services' application logic using rules and context. Moreover, it collects sensor data and produces the context information that is required for the rules. The authors present the architecture, design, complete implementation, and prototype‐based verification of perception framework.

Development of context‐aware services is achieved with a novel architecture supporting building of the logic of web services using rules which directly manipulate the available elementary context represented with the Web Ontology Language (OWL) ontology. These rules are described using the Rule Interchange Format (RIF) with support for different rule languages. The implementation of this framework is aligned with RESTful principles, providing a lightweight and flexible solution for large‐scale context‐aware systems.

The fully implemented prototype verifies the feasibility of constructing the logic of context‐aware web services with the rules supported by perception framework.

The contributions of this paper include: the requirement specification for a generic context‐aware pervasive middleware; and the design and implementation of the framework (i.e. perception framework) supporting the development of context‐aware web services. The perception framework includes a generic rule‐based reasoner allowing developers to use several RIF‐compliant rule description languages.

The rapid proliferation of mobile context aware applications has resulted in an increased research interest towards developing specialized context data management strategies for mobile entities. The purpose of this paper is to aim to develop a new way to model mobile entities and manage their contexts accordingly.

This paper proposes the concept of “Mobile Space” to model mobile entities and presents strategies to manage the various contexts associated therein. To handle availability related issues, two system services are designed: the “Availability Updating Service” which is an identifier based mechanism and is designed to keep track of mobile objects and handle availability related issues, and the “Application Callback Service” which is a publish/subscribe based mechanism to handle application disruptions and interruptions arising due to mobility.

The paper presents a detailed study of the proposed framework and a description of the underlying services and the components therein to validate the framework. Experimental results carried out in WiFi and 3G environments indicate that the proposed techniques can support mobile applications and minimize application disruptions with minimal overhead.

The proposed context management framework is generic in nature and is not designed for a specific class of applications. Any mobile context aware application can leverage on the framework and utilize the provided functionalities to manage application disruptions. Also, the decoupling of mobile application layer and the underlying context data management layer renders context data management layer transparent to the application design.

A decade and a half after the debut of pervasive computing, a large number of prototypes, applications, and interaction interfaces have emerged. However, there is a lack of consensus about the best approaches to create such systems or how to evaluate them. To address these issues, this paper aims to develop a performance evaluation framework for pervasive computing systems.

Based on the authors' experience in the Gator Tech Smart House – an assistive environment for the elderly, they established a reference scenario that was used to guide the analysis of the large number of systems they studied. An extensive survey of the literature was conducted, and through a thorough analysis, the authors derived and arrived at a broad taxonomy that could form a basic framework for evaluating existing and future pervasive computing systems.

A taxonomy of pervasive systems is instrumental to their successful evaluation and assessment. The process of creating such taxonomy is cumbersome, and as pervasive systems evolve with new technological advances, such taxonomy is bound to change by way of refinement or extension. This paper found that a taxonomy for something so broad as pervasive systems is very complex. It overcomes the complexity by focusing the classifications on key aspects of pervasive systems, decided purely empirically and based on the authors own experience in a real‐life, large‐scale pervasive system project.

There are currently no methods or frameworks for comparing, classifying, or evaluating pervasive systems. The paper establishes a taxonomy – a first step toward a larger evaluation methodology. It also provides a wealth of information, derived from a survey of a broad collection of pervasive systems.

The emergence of radio frequency identification (RFID) technology promises enormous opportunities to shift business process automation up to the wire level. The purpose of this paper is to explore the methodology of incorporating business logics into RFID edge systems, and thereby facilitate the business process automation in the RFID‐applied environment.

Following the object‐oriented modelling perspective, concepts of classes, instances are deployed to characterise the runtime context of RFID business scenarios; event patterns are used to aggregate RFID tag read events into business meaningful events; and business rules are established to automate business transactions according to the elicited events.

The paper has emphasised the synergy between business process automation and automatic data acquisition, and has identified the inter‐relations between RFID tag read events, application‐level events, business rules, and business operations. The reported research has demonstrated a feasible scheme of incorporating business process control and automation into RFID‐enabled applications.

The paper analyses the characteristics of RFID data and event handling in relation to business rule modelling and process automation. The features of event‐relied awareness, context containment and overlapping, etc. are all captured and described by the proposed object‐oriented business model. The given data‐driven RFID middleware architecture can serve as one reference architecture for system design and development. Hence, the paper plays an important role in connecting automatic data acquisition and existing business processes, and thereby bridges the physical world and the digital world.