A Uniform Device Information Access for Context-Aware Middleware

This paper presents a middleware for building context-aware applications. One of the main components, Device Information Access (DIA), is discussed in detail. Since many kinds of devices (e.g., RFID, GPS, Bluetooth, etc.) can be used to collect the context information, the middleware defines the Device Information Access component to communicate with different devices. A set of interfaces are devised in DIA, and the common functions such as getting and setting a data element are defined in the interfaces. For each device, we shall provide an implementation of the interfaces to communicate with the corresponding servers or software agents. DIA can communicate with the software agents or servers using various protocols such as RMI, Web Services, and REST. In this way the access to the hardware are encapsulated by the middleware and virtualized to the end-point App ications. The architecture of the middleware and the functions of DIA are discussed, and an empirical application is also developed to validate our design. ? 2010 IEEE.EI

Context awareness for collaborative learning with uncertainty management

Postprint (published version

Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks

PublishedJournal Article© 2014 IEEE. Coverage of interest points and network connectivity are two main challenging and practically important issues of Wireless Sensor Networks (WSNs). Although many studies have exploited the mobility of sensors to improve the quality of coverage andconnectivity, little attention has been paid to the minimization of sensors' movement, which often consumes the majority of the limited energy of sensors and thus shortens the network lifetime significantly. To fill in this gap, this paper addresses the challenges of the Mobile Sensor Deployment (MSD) problem and investigates how to deploy mobile sensors with minimum movement to form a WSN that provides both target coverage and network connectivity. To this end, the MSD problem is decomposed into two sub-problems: the Target COVerage (TCOV) problem and the Network CONnectivity (NCON) problem. We then solve TCOV and NCON one by one and combine their solutions to address the MSD problem. The NP-hardness of TCOV is proved. For a special case of TCOV where targets disperse from each other farther than double of the coverage radius, an exact algorithm based on the Hungarian method is proposed to find the optimal solution. For general cases of TCOV, two heuristic algorithms, i.e., the Basic algorithm based on clique partition and the TV-Greedy algorithm based on Voronoi partition of the deployment region, are proposed to reduce the total movement distance ofsensors. For NCON, an efficient solution based on the Steiner minimum tree with constrained edge length is proposed. Thecombination of the solutions to TCOV and NCON, as demonstrated by extensive simulation experiments, offers a promising solutionto the original MSD problem that balances the load of different sensors and prolongs the network lifetime consequently.This work is supported in part by the National Science Foundation of China (Grant Nos. 61232001, 61103203, 61173169, and 61173051), the Major Science & Technology Research Program for Strategic Emerging Industry of Hunan (Grant No. 2012GK4054), and the Scientific Research Fund of Hunan Provincial Education Department (Grant No. 14C0030)

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work

Context modelling for natural Human Computer Interaction applications in e-health

The conception of IoT (Internet of Things) is accepted as the future tendency of Internet among academia and industry. It will enable people and things to be connected at anytime and anyplace, with anything and anyone. IoT has been proposed to be applied into many areas such as Healthcare, Transportation，Logistics, and Smart environment etc. However, this thesis emphasizes on the home healthcare area as it is the potential healthcare model to solve many problems such as the limited medical resources, the increasing demands for healthcare from elderly and chronic patients which the traditional model is not capable of. A remarkable change in IoT in semantic oriented vision is that vast sensors or devices are involved which could generate enormous data. Methods to manage the data including acquiring, interpreting, processing and storing data need to be implemented. Apart from this, other abilities that IoT is not capable of are concluded, namely, interoperation, context awareness and security & privacy. Context awareness is an emerging technology to manage and take advantage of context to enable any type of system to provide personalized services. The aim of this thesis is to explore ways to facilitate context awareness in IoT. In order to realize this objective, a preliminary research is carried out in this thesis. The most basic premise to realize context awareness is to collect, model, understand, reason and make use of context. A complete literature review for the existing context modelling and context reasoning techniques is conducted. The conclusion is that the ontology-based context modelling and ontology-based context reasoning are the most promising and efficient techniques to manage context. In order to fuse ontology into IoT, a specific ontology-based context awareness framework is proposed for IoT applications. In general, the framework is composed of eight components which are hardware, UI (User Interface), Context modelling, Context fusion, Context reasoning, Context repository, Security unit and Context dissemination. Moreover, on the basis of TOVE (Toronto Virtual Enterprise), a formal ontology developing methodology is proposed and illustrated which consists of four stages: Specification & Conceptualization, Competency Formulation, Implementation and Validation & Documentation. In addition, a home healthcare scenario is elaborated by listing its well-defined functionalities. Aiming at representing this specific scenario, the proposed ontology developing methodology is applied and the ontology-based model is developed in a free and open-source ontology editor called Protégé. Finally, the accuracy and completeness of the proposed ontology are validated to show that this proposed ontology is able to accurately represent the scenario of interest

Inconsistency Detection and Resolution for Context-Aware Middleware Support

Context-awareness is a key feature of pervasive computing whose environments keep evolving. The support of context-awareness requires comprehensive management including detection and resolution of context inconsistency, which occurs naturally in pervasive computing. In this paper we present a framework for realizing dynamic context consistency management. The framework supports inconsistency detection based on a semantic matching and inconsistency triggering model, and inconsistency resolution with proactive actions to context sources. We further present an implementation based on the Cabot middleware. The feasibility of the framework and its performance are evaluated through a case study and a simulated experiment, respectively