Dynamic Context Information Research Articles

A Framework for Exploiting Internet of Things for Context-Aware Trust-Based Personalized Services

In the last years, we have witnessed the introduction of the Internet of Things (IoT) as an integral part of the Internet with billions of interconnected and addressable everyday objects. On one hand, these objects generate a massive volume of data that can be exploited to gain useful insights into our day-to-day needs. On the other hand, context-aware recommender systems (CARSs) are intelligent systems that assist users to make service consumption choices that satisfy their preferences based on their contextual situations. However, one of the key challenges facing the development and deployment of CARSs is the lack of functionality for providing dynamic and reliable context information required by the recommendation decision process. Thus, data obtained from IoT objects and other sources can be exploited to build CARSs that satisfy users’ preferences, improve quality of experience, and boost recommendation accuracy. This article describes various components of a conceptual IoT-based framework for context-aware personalized recommendations. The framework addresses the weakness whereby CARSs rely on static and limited contexts from user’s mobile phone by providing additional components for reliable and dynamic context information, using IoT context sources. The core of the framework consists of a context classification and reasoning management and a dynamic user profile model, incorporating trust to improve the accuracy of context-aware personalized recommendations. Experimental evaluations show that incorporating context and trust into personalized recommendation process can improve accuracy.

Dynamic mobile cloud offloading prediction based on statistical regression

Due to the advancement of mobile technology, a large number of computationally intensive applications are created for smart phones. But the limitations of battery and processing power of smart phones are making it inferior to laptops and desktop computers. Mobile Cloud Offloading (MCO) allows the s mart phones to offload computationally intensive tasks to the cloud, making it more effective in terms of energy, speed or both. Increased networking capacity due to the availability of high speed Wi-Fi and cellular connections like 3G/4G makes offloading more efficient. Even then, the choice of offloading is not always advisable, because of the highly dynamic context information of mobile devices and clouds. In this paper, we propose a dynamic decision making system, which will decide whether to offload or do the tasks locally, depending on the current context information and the optimization choice of the user. Metrics are developed for time, energy and combination of time and energy to assess the proposed system. A test bed is implemented and the results are showing improvements from the currently existing methods.

Dynamic Computation of Time-Varying Spatial Contexts

There are many real-life processes whose smart control requires processing context information. Though processing time-varied context information is addressed in the literature, domain-independent solutions for reasoning about time-varying process scenarios are scarce. This paper proposes a method for dynamic context computation concerning spatial and attributive information. Context is interpreted as a body of information dynamically created by a pattern of entities and relationships over a history of situations. Time is conceived as a causative force capable of changing situations and acting on people and objects. The invariant and variant spatial information is captured by a two-dimensional spatial feature representation matrix (SFR-matrix). The time-dependent changes in the context information are computed based on a dynamic context information (DCI) management hyper-matrix. This humble but powerful representation lends itself to a quasi-real time computing and is able to provide information about foreseeable happenings over multiple situations. Based on this, the reasoning mechanism proposed in this paper is able to provide informative instructions for users who needed to be informed in a dynamically changing situation. This paper uses the practical case of evacuation of a building in fire both as an explorative case for conceptualization of the functionality of the computational mechanism and as a demonstrative and testing application. Our intention is to use the dynamic context computation mechanism as a kernel component of a reasoning platform for informing cyber-physical systems (I-CPSs). Our future research will address the issue of context information management for multiple interrelated spaces.

Pull-based recommendations in mobile environments

In the field of Context-Aware Recommendation Systems (CARS), only static contextual information is usually considered. However, the dynamic contextual information would very helpful in mobile computing scenarios. Despite this interest, the design and implementation of flexible and generic frameworks to support an easy development of context-aware mobile recommendation systems have been relatively unexplored. In this paper, we describe a framework that facilitates the development of CARS for mobile environments. We mainly focus on the development of the elements needed to support pull-based recommendations and the experimental evaluation of the proposed system.

OntCAAC: An Ontology-Based Approach to Context-Aware Access Control for Software Services

In modern communication environments, the ability to provide access control to services in a context-aware manner is crucial. By leveraging the dynamically changing context information, we can achieve context-specific control over access to services, better satisfying the security and privacy requirements of the stakeholders. In this paper, we introduce a new Context-Aware Access Control (CAAC) Framework that adopts an ontological approach in modelling dynamic context information and the corresponding CAAC policies. It includes a context model specific to access control, capturing the relevant low-level context information and inferring the high-level implicit context information. Using the context model, the policy model of the framework provides support for specifying and enforcing CAAC policies. We have developed a prototype and presented a healthcare case study to realise the framework.

Research on Multi-Level Context-Aware Material Data Model within Manufacturing Enterprises

Context-aware applications can sense and explore the context of production processes to provide proper and useful services to managers in workshop. And materials data integration and control are one of core competences concerning with the development of mass data application in manufacturing enterprises. In this paper, a context-aware materials data integration meta model is presented which is incorporating an advanced materials demand mapping and decomposition mechanism to support fine-grained materials data in the right time for the provision of materials services, based on the analysis of the application context involving the key points and relationships in their manufacturing processes. In this model, materials data integration is controlled by the demand state transitions at different levels including workflow levels, control levels and data levels, which incorporates dynamic context information by checking the context constraint associated with each application task at the time of the specific request submission. Finally, a case is given which is implemented in a complex equipments enterprise.

Investigation of a hierarchical context-aware architecture for rule-based customisation of mobile computing service

The continuous technical progress in mobile device built-in modules and embedded sensing techniques creates opportunities for context-aware mobile applications. The context-aware computing paradigm exploits the relevant context as implicit input to characterise the user and physical environment and provide a computing service customised to the contextual situation. However, heterogeneity in techniques, complexity of contextual situation, and gap between raw sensor data and usable context keep the techniques from truly integration for extensive use. Studies in this area mainly focus on feasibility demonstration of the emerging techniques, and they lack general architecture support and appropriate service customisation strategy. This investigation aims to provide general system architecture and technical approaches to deal with the heterogeneity problem and efficiently utilise the dynamic context towards proactive computing service that is customised to the contextual situation. The main efforts of this investigation are the approaches to gathering, handling, and utilising the dynamic context information in an efficient way and the decision making and optimisation methods for computing service customisation. In brief, the highlights of this thesis cover the following aspects: (1) a hierarchical context-aware computing architecture supporting interoperable distribution and further use of context; (2) an in-depth analysis and classification of context and the corresponding context acquisition methods; (3) context modelling and context data representation for efficient and interoperable use of context; (4) a rule-based service customisation strategy with a rule generation mechanism to supervise the service customisation. In addition, feasibility demonstration of the proposed system and contribution justification of this investigation are conducted through case studies and prototype implementations. One case study uses mobile built-in sensing techniques to improve the usability and efficiency of mobile applications constrained by resource limitation, and the other employs the mobile terminal and embedded sensing techniques to predict users’ expectations for home facility automatic control. Results demonstrate the feasibility of the proposed context handling architecture and service customisation methods. It shows great potential for employing the context of the computing environment for context-aware adaptation in pervasive and mobile applications but also indicates some underlying problems for further study.

Network aware dynamic context subscription management

Context-awareness is a key requirement in many of today’s networks, services and applications. Context management systems are used to provide access to distributed, dynamic context information. The reliability of remotely accessed dynamic context information is impacted by network delay, packet drop probability, its information dynamics and the access strategy used. Due to the characteristics of the different access strategies, different levels of reliability of context information can be ensured, but at the same time, these strategies lead to different access traffic which impacts also the network performance, and hence feeds back to the reliability of the information. Furthermore, different levels of QoS may be available and used in order to mitigate the impact of network performance degradation on the reliability of the dynamic context information. In this paper we describe a system and algorithms that are capable of configuring effectively context access strategies in order to maximize reliability of all accessed dynamic context information. The framework utilizes and extends existing information reliability models, and it can utilize different network performance models. Simulation results of scenarios in which the framework uses finite-buffer bottleneck performance models demonstrate the effectiveness of our algorithm to increase reliability. Furthermore, the framework is applied to a scenario with QoS classes that allows to trade off delay and loss via different buffer-size configurations.

Dynamic Context-Aware System Based on Multi-Level Material Data Control Model

Context-aware applications can sense and explore the context of production processes to provide proper and useful services to managers in workshop. Firstly, a multi-level ontology model of materials is found which is expressed in OWL as an ontology collection of describing places ages and events and associated properties among them. Secondly, a multi-level context-aware control model and its mechanism are produced. In this model, data integration is controlled by the demand state transitions at different levels including workflow levels, control levels and data levels, which incorporates dynamic context information. And context is classified based on the analysis of demand into five main categories, which is further categorized as simple condition and composite condition to form a multi-level context. And the data integration model is implemented dynamically by checking the context constraint associated with each application task at the time of the specific request submission. Finally, a case study is developed within a manufacturing enterprise to show the benefits of the model.

Material Data Integration Model Based on Context-Aware within Manufacturing Enterprises

Materials data integration is one of core competence concerning with the development of mass data application in manufacture enterprises. In this paper, a context-aware materials data integration meta model is presented which is incorporating an advanced materials demand mapping and decomposition mechanism to support fine-grained materials data in the right time for the provision of materials services, based on the analysis of the application context involving the key points and relationships in their manufacturing processes. In this model, materials data integration is controlled by the demand state transitions at different levels including workflow levels, control levels and data levels, which incorporates dynamic context information by checking the context constraint associated with each application task at the time of the specific request submission. Finally, a case is given which is implemented in a complex equipments enterprise.

Scalable Management of Trajectories and Context Model Descriptions

The ongoing proliferation of sensing technologies constitutes a huge potential for context-aware computing. It allows selecting relevant information about our physical environment from different sources and providers all over the globe. A fundamental challenge is how to provide efficient access to these immense amounts of distributed dynamic context information – particularly due to the mobility of devices and other entities. To enable such access to current and past position information about moving objects, we propose a family of protocols (CDR, GRTS) for efficiently tracking a moving objects trajectory at some remote database in real-time as well as a distributed indexing scheme (DTI) for optimized access to trajectory data that is partitioned in space to multiple database servers. For discovering context information that is relevant for the situation of an application, we propose a powerful formalism for describing context models in a concise manner and a tailored multidimensional data structure (SDC-Tree) for retrieving relevant context models out of potentially millions of descriptions.

Context-based user grouping for multi-casting in heterogeneous radio networks

Abstract. Along with the rise of sophisticated smartphones and smart spaces, the availability of both static and dynamic context information has steadily been increasing in recent years. Due to the popularity of social networks, these data are complemented by profile information about individual users. Making use of this information by classifying users in wireless networks enables targeted content and advertisement delivery as well as optimizing network resources, in particular bandwidth utilization, by facilitating group-based multi-casting. In this paper, we present the design and implementation of a web service for advanced user classification based on user, network, and environmental context information. The service employs simple and advanced clustering algorithms for forming classes of users. Available service functionalities include group formation, context-aware adaptation, and deletion as well as the exposure of group characteristics. Moreover, the results of a performance evaluation, where the service has been integrated in a simulator modeling user behavior in heterogeneous wireless systems, are presented.

Context-aware media independent information server for optimized seamless handover procedures

The proliferation of the Internet and wireless access technologies introduced the constant mobile paradigm, in which users want to be always connected making use of the best available networks and technologies. In order to provide seamless connectivity among the new wireless access technologies, such as Wi-Fi, WiMAX and 3GPP (UMTS, HSPA and/or LTE), the IEEE 802.21 standard has defined the media independent handover framework. However, although there is a recognized importance of the IEEE 802.21 framework in the vertical handover optimization procedures, it is still necessary to improve this insofar as the radio access technologies individual features are concerned. Moreover, the IEEE 802.21 standard defines an information server that is only able to manage static network information. It is clear that in current and future environments, dynamic context information from network side entities is very important for the vertical handover decision procedures. This paper presents the integration process of the MIH framework with the aforesaid wireless access technologies, enabling the complete support of all the envisioned IEEE 802.21 handover phases. It describes how IEEE 802.21 can be adapted to the specific characteristics of the access technologies, and the mechanisms required to perform the several handover phases between Wi-Fi, WiMAX and 3GPP. Furthermore, this paper addresses a new concept of a context-aware information server that is able to store, manage and deliver real-time dynamic information retrieved from both the network and the terminal side entities, such as the user preferences, running services, mobile nodes characteristics and available network resources. The purpose of this context-aware information server is to optimize the handover preparation and decision phases. Additionally, a meticulous evaluation of the depicted handover mechanisms optimized by the IEEE 802.21 framework is presented, demonstrating that seamless handover between WiMAX, Wi-Fi and 3GPP access networks is achieved with low latency and no packet loss. Finally, the benefits of integrating a context-aware information server in the seamless handover procedure are also evaluated. To perform this evaluation, significant add-ons, also described in this paper, were implemented in the NS-2 simulator to support all the functionalities defined by the IEEE 802.21 standard, as well as the proposed extensions to the standard.

Context-awareness for heterogeneous access management

Abstract. The increasing availability of both static and dynamic context information has steadily been driving the development of context-aware communication systems. Adapting system behavior according to current context of the network, the user, and the terminal can yield significant end-to-end performance improvements. In this paper, we present a concept for how to use context information, in particular location information and movement prediction, for Heterogeneous Access Management (HAM). In a first step, we outline the functional architecture of a distributed and extensible context management system (CMS) that defines the roles, tasks, and interfaces of all modules within such a system for large-scale context acquisition and dissemination. In a second step, we depict how the available context information can be exploited for optimizing terminal handover decisions to be made in a multi-RAT (radio access technology) environment. In addition, the utilized method for predicting terminal location as well as the objective functions used for evaluating and comparing system performance are described. Finally, we present preliminary simulation results demonstrating that HAM systems that include current and future terminal context information in the handover decision process clearly outperform conventional systems.

Context Aware Service System Supported the Collaborative Management of Distribution Task

Distribution tasks have typical feature of context dependence. Attaining the mission-related dynamic context information service timely and accurately has a significant effect to the execution efficiency of the distribution task. On the basis of the definition of four distribution contexts systematically: network context , product context, customer context, resource context, this paper proposes the model of context management of distribution task, and the collaborative service and process mechanism of distribution tasks base on task context, it is of great value and significance to support the effective implementation of collaborative management of the distribution task in dynamic environment.

Relation-Based Access Control: An Access Control Model for Context-Aware Computing Environment

Context-aware computing is an important aspect of the pervasive computing environment and its various dynamic context information brings new challenges to access control systems. In this paper a new access control model, relation based access control (RelBAC), is provided for context-aware environment with a domain specific Description Logic to formalize the model. The novelty of RelBAC is that permissions are formalized as binary relations between subjects and objects which could evolve with the dynamic contexts. The expressive power of RelBAC is illustrated in a case study of a project meeting event.

On the Design and Prototype Implementation of a Multimodal Situation Aware System

In this paper we describe the design concepts and prototype implementation of a situation aware ubiquitous computing system using multiple modalities such as National Marine Electronics Association (NMEA) data from Global Positioning System (GPS) receivers, text, speech, environmental audio, and handwriting inputs. While most mobile and communication devices know where and who they are, by accessing context information primarily in the form of location, time stamps, and user identity, the concept of sharing of this information in a reliable and intelligent fashion is crucial in many scenarios. A framework which takes the concept of context aware computing to the level of situation aware computing by intelligent information exchange between context aware devices is designed and implemented in this work. Four sensual modes of contextual information like text, speech, environmental audio, and handwriting are augmented to conventional contextual information sources like location from GPS, user identity based on IP addresses (IPA), and time stamps. Each device derives its context not necessarily using the same criteria or parameters but by employing selective fusion and fission of multiple modalities. The processing of each individual modality takes place at the client device followed by the summarization of context as a text file. Exchange of dynamic context information between devices is enabled in real time to create multimodal situation aware devices. A central repository of all user context profiles is also created to enable self-learning devices in the future. Based on the results of simulated situations and real field deployments it is shown that the use of multiple modalities like speech, environmental audio, and handwriting inputs along with conventional modalities can create devices with enhanced situational awareness.

Binary analysis for measurement and attribution of program performance

Modern programs frequently employ sophisticated modular designs. As a result, performance problems cannot be identified from costs attributed to routines in isolation; understanding code performance requires information about a routine's calling context. Existing performance tools fall short in this respect. Prior strategies for attributing context-sensitive performance at the source level either compromise measurement accuracy, remain too close to the binary, or require custom compilers. To understand the performance of fully optimized modular code, we developed two novel binary analysis techniques: 1) on-the-fly analysis of optimized machine code to enable minimally intrusive and accurate attribution of costs to dynamic calling contexts; and 2) post-mortem analysis of optimized machine code and its debugging sections to recover its program structure and reconstruct a mapping back to its source code. By combining the recovered static program structure with dynamic calling context information, we can accurately attribute performance metrics to calling contexts, procedures, loops, and inlined instances of procedures. We demonstrate that the fusion of this information provides unique insight into the performance of complex modular codes. This work is implemented in the HPCToolkit performance tools (http://hpctoolkit.org).

COMPACT: Middleware for context representation and management in pervasive computing

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.

A dynamic context-aware access control architecture for e-services

The universal adoption of the Internet and the emerging web services technologies constitutes the infrastructure that enables the provision of a new generation of e-services and applications. However, the provision of e-services through the Internet imposes increased risks, since it exposes data and sensitive information outside the client premises. Thus, an advanced security mechanism has to be incorporated, in order to protect this information against unauthorized access. In this paper, we present a context-aware access control architecture, in order to support fine-grained authorizations for the provision of e-services, based on an end-to-end web services infrastructure. Access permissions to distributed web services are controlled through an intermediary server, in a completely transparent way to both clients and protected resources. The access control mechanism is based on a Role-Based Access Control (RBAC) model, which incorporates dynamic context information, in the form of context constraints. Context is dynamically updated and provides a high level of abstraction of the physical environment by using the concepts of simple and composite context conditions. Also, the paper deals with implementation issues and presents a system that incorporates the proposed access control mechanism in a web services infrastructure that conform to the OPC XML-DA specification.