Context-sensitive Services Research Articles

Designing Security for the Sixth Generation: About Necessity, Concepts and Opportunities

Intelligent, comprehensive and, above all, secure wireless interconnection is the driving force behind technological progress. To ensure this, the development towards Sixth Generation (6G) Wireless Systems has been launched and is scheduled to be operational by 2030. This data technology of the future turns 6G into the infrastructure of a new generation of mobile, intelligent, and context-sensitive services, available everywhere and featuring high trustworthiness and performance, relying on both, network-side and off-network context sources. In addition, the networks themselves ought to become intelligent and thus more efficient and resource-saving, which requires a high degree of automated utilization of Artificial Intelligence (AI). Building upon the principles of information and communication theory for both the physical (bit)-transmission layer (PHY) and media access, new communication concepts for 6G will be developed providing the foundations for research into new single and multi-user operation, access and core networks. The flip side of this coin of opportunities: Sophisticated technology inevitably leads to additional security vulnerabilities, open access systems and Open-Radio Access Network (O-RAN) approaches imply new attack vectors. The holistic interconnection of everything renders it ever more attractive to attackers to harm systems, and create damage. Furthermore, enhanced computational power along with quantum computers make conventional systems more vulnerable than ever, and the value of the transmitted data increases tremendously: It is not only machine and sensor data, but also very personal and healthcare data transmitted with 6G. Therefore, the aim is to build a resilient and secure 6G system capable of recognizing attacks and uncertainties, flexibly absorbing them, recovering in a timely and sustainable manner, and compensating for impaired functionality through transformation. This holistic resilience-by-design approach is based, among other things, on technology such as Quantum Key Distribution (QKD) and Post Quantum-Crypto to achieve end-to-end security, Reconfigurable Intelligent Surfaces (RISs) to rely, control and manipulate the wireless transmission channel, Wireless Optical Communication (WOC), Physical Layer Security (PhySec), but also Body Area Networks (BANs), the integration of the human body relying on biometrics and the Tactile Internet (TI). These concepts will be discussed and shed light on in the scope of this work.

Enabling civil–military collaboration for disaster relief operations in smart city environments

To address the aftermath of ever more frequent natural disasters striking highly-populated urban areas, Humanitarian Assistance and Disaster Relief (HADR) operations increasingly involve the coordinated efforts of multiple agencies and in particular Civil–Military Cooperation (CIMIC). In such scenarios, rescuers operate in a disrupted environment, must maintain a high operational tempo, and need to quickly make high-impact decisions. Effectively supporting emergency responders through IT services that implement accurate situation awareness presents a formidable set of challenges, including the discovery and integration of surviving IT assets with purposely deployed ones; effective information prioritization; resilient communications; and secure information sharing. We believe that in the highly digital modern urban environment, often referred to as smart cities, these challenges can be effectively addressed only by integrating by design HADR support into the smart city middleware. This paper presents Aceso — a proof-of-concept smart city middleware that provides location- and context-sensitive services with full support for HADR operations. Aceso provides a set of functions, ranging from resource discovery to secure information sharing, that can be quickly activated in case of unpredictable and adverse events to facilitate HADR operations. Furthermore, Aceso leverages the Value-of-Information (VoI) methodology to handle the processing and dissemination of mission-critical information. To validate the capabilities of Aceso, we devised a fictional HADR scenario, set in the city of Helsinki, Finland, that involves the collaboration of multiple responder teams with different roles. The validation results confirm Aceso’s usefulness in prioritizing the processing and dispatching of critical information and in realizing federation-wide sharing of this information among HADR teams.

Context-Aware Service Recommendation Based on Knowledge Graph Embedding

Over two decades, context awareness has been incorporated into recommender systems in order to provide, not only the top-rated items to consumers but also the ones that are suitable to the user context. As a class of context-aware systems, context-aware service recommendation (CASR) aims to bind high-quality services to users, while taking into account their context requirements, including invocation time, location, social profiles, connectivity, and so on. However, current CASR approaches are not scalable with the huge amount of service data (QoS and context information, users reviews and feedbacks). In addition, they lack a rich representation of contextual information, as they adopt a simple matrix view. Moreover, current CASR approaches adopt the traditional user-service relation and they do not allow for multi-relational interactions between users and services in different contexts. To offer a scalable and context-sensitive service recommendation with great analysis and learning capabilities, we provide a rich and multi-relational representation of the CASR knowledge, based on the concept of knowledge graph. The constructed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">context-aware service knowledge graph</i> (C-SKG) is, then, transformed into a low-dimensional vector space to facilitate its processing. For this purpose, we adopt Dilated Recurrent Neural Networks to propose a context-aware knowledge graph embedding, based on the principles of first-order and subgraph-aware proximity. Finally, a recommendation algorithm is defined to deliver the top-rated services according to the target user's context. Experiments have proved the accuracy and scalability of our solution, compared to state-of-the-art CASR approaches.

Engineering Privacy in Smartphone Apps: A Technical Guideline Catalog for App Developers

With the rapid growth of technology in recent years, we are surrounded by or even dependent on the use of technological devices such as smartphones as they are now an indispensable part of our life. Smartphone applications (apps) provide a wide range of utilities such as navigation, entertainment, fitness, etc. To provide such context-sensitive services to users, apps need to access users’ data including sensitive ones, which in turn, can potentially lead to privacy invasions. To protect users against potential privacy invasions in such a vulnerable ecosystem, legislation such as the European Union General Data Protection Regulation (EU GDPR) demands best privacy practices. Therefore, app developers are required to make their apps compatible with legal privacy principles enforced by law. However, this is not an easy task for app developers to comprehend purely legal principles to understand what needs to be implemented. Similarly, bridging the gap between legal principles and technical implementations to understand how legal principles need to be implemented is another barrier to develop privacy-friendly apps. To this end, this paper proposes a privacy and security design guide catalog for app developers to assist them in understanding and adopting the most relevant privacy and security principles in the context of smartphone apps. The presented catalog is aimed at mapping the identified legal principles to practical privacy and security solutions that can be implemented by developers to ensure enhanced privacy aligned with existing legislation. Through conducting a case study, it is confirmed that there is a significant gap between what developers are doing in reality and what they promise to do. This paper provides researchers and developers of privacy-related technicalities an overview of the characteristics of existing privacy requirements needed to be implemented in smartphone ecosystems, on which they can base their work.

Implementing community-based health promotion in socio-economically disadvantaged areas: a qualitative study.

There is a gradient relationship between socio-economic status and health. We investigated the views and perceptions of health promotion service providers regarding factors that affect lack of engagement in public health initiatives by residents in socio-economically disadvantaged (SED) communities. We conducted semi-structured interviews with a purposive sample of key providers (n=15) of community-based health promotion services to elicit their views about engagement-related factors and their experiences of the provision, delivery and impact of health promotion in SED areas. Interviews were analysed using thematic analysis. Failure to (i) recognise within SED communities, socio-cultural norms of health-related behaviour and (ii) communicate to local residents an understanding of complex lifestyle influences appeared to affect adversely service engagement and contribute to the development of negative attitudes towards health promotion. Engagement is more likely when services are delivered within familiar settings, peer support is available, initiatives are organized within existing groups, external incentives are offered and there are options regarding times and locations. Collaborative working between providers and communities facilitates efficient, context-sensitive service delivery. Knowledge of a local community and its socio-environmental context alongside a collaborative, facilitative and tailored approach to delivery are required to ensure successful engagement of SED communities in health promotion.

IoT in the Fog: A Roadmap for Data-Centric IoT Development

Our interactions with the world are increasingly dependent on context-aware services, and the future of smart cities is coupled with how efficiently and reliably we can deliver these services to end users. In this article we present the premise of personalized IoT systems, by leveraging novel advancements in user-centric technologies under the fog computing architecture. This means leveraging the connectivity and processing potential of the fog to bring IoT control and analytics closer to the user, and improve the coupling of services with local IoT components in user-centric contexts. The potential gain in access latency and context-sensitive service matching will enable a multitude of smart city services. On one hand, data management (collection, pruning, denaturing [1], and encryption) can take place closer to the edge, thereby leveraging network load and service times. On the other hand, service matching in smart city applications will witness higher responsiveness and resource visibility in areas with intermittent connectivity or high mobility. We first present the challenges in migrating cloud-IoT architectures to the network edge, and detail the hindrances in transitioning the control and management of IoT systems to the user end. As a remedy, we survey recent advancements in the IoT, ubiquitous computing, and user-centric services, which enable us to advance personalized IoT architectures. We finally present a framework for IoT in the fog to synergize these advancements, and present a proof-of-concept use case to highlight its utility and impact. We conclude this article with prime directions for future work to realize a personalized IoT architecture, and highlight the potential gain in prioritizing five high-yield potential research issues.

A Context-Sensitive Service Composition Framework for Dependable Service Provision in Cyber-Physical Systems

Most of the service-oriented architecture-based mechanisms for web services are insufficient to support-dependable service composition with the heterogeneous, dynamic physical entities in a cyber-physical system (CPS). Taking into account the contexts of physical entities, this paper presents a context-sensitive service composition framework in a CPS with dependability requirements. First, an ontology model for context-sensitive service specification of physical entities is proposed. Then, a service workflow spanning graph SWSG is used to map the workflow based abstract process model of a given task to multiple sets of atomic service instances. Finally, we present a two-phase context-sensitive service composition optimisation mechanism, which is able to select out the optimal service providers to implement the task effectively and dependably. The experiment results show that the precision and efficiency of service discovery, the success ratio of workflow execution and the performance of service combination optimisation have been greatly improved with our proposed method.

A context-sensitive service composition framework for dependable service provision in cyber-physical systems

A context-sensitive service composition framework for dependable service provision in cyber-physical systems

Supporting Context Sensitive Lean Product Service Engineering

Modern companies face immense market pressure to meet customers’ demands while ensuring the sustainability of business. Consumers are now requesting highly customized products and services, i.e. demanding mass customization from manufacturing companies. The complete value chain needs to develop strategies enabling interaction with customers and consumers, supporting customization of features and services, and even co-design. This paper presents the DIVERSITY approach, which consists on a methodology and engineering environment supporting companies in using social media to realize a context sensitive lean design process of product service systems.

EFRIEND: an ethical framework for intelligent environments development

Intelligent environments aim to provide context-sensitive services to humans in the physical spaces in which they work and live. While the ethical dimensions of these systems have been considered, this is an aspect which requires further analysis. A literature review shows that these approaches are disconnected from each other, and that they are making little impact on real systems being built. This article provides a solution to both of these problems. It synthesises the ethical issues addressed by previous work and highlights other important concerns which have been overlooked so far. Furthermore, it proposes an alternative, more holistic approach that can be used to guide the development of intelligent environments. The validity of the framework is demonstrated by its integration into an actual project.

The Bluejay Genome Browser

The Bluejay genome browser is a stand-alone visualization tool for the multi-scale viewing of annotated genomes and other genomic elements. Bluejay allows users to customize display features to suit their needs, and produces publication-quality graphics. Bluejay provides a multitude of ways to interrelate biological data at the genome scale. Users can load gene expression data into a genome display for expression visualization in context. Multiple genomes can be compared concurrently, including time series expression data, based on Gene Ontology labels. External, context-sensitive biological Web Services are linked to the displayed genomic elements ad hoc for in-depth genomic data analysis and interpretation. Users can mark multiple points of interest in a genome by creating waypoints, and exploit them for easy navigation of single or multiple genomes. Using this comprehensive visual environment, users can study a gene not just in relation to its genome, but also its transcriptome and evolutionary origins. Written in Java, Bluejay is platform-independent and is freely available from http://bluejay.ucalgary.ca.

A self-optimizing QoS-aware service composition approach in a context sensitive environment

QoS-aware service composition is aimed to maximize the global QoS of a composite service when selecting candidate services. In a context sensitive service execution environment in pervasive computing, the context information for service composition is not static: device, policy, and user constraints, and QoS requirements may change, new services may be deployed, old ones withdrawn, or existing ones change their QoS parameters. This results in the current service composition plan failing or its QoS degrading from the optimum. In this paper, a runtime self-optimizing service composition framework is proposed. An implementation of a prototype for this framework is presented, addressing the issues of reducing extra delay while increasing global QoS in service composition in a dynamic context environment. Three service re-plan algorithms are compared that can be used in dynamic context environment, i.e., minimal-conflict hill-climbing repair genetic algorithm (MCHC-repair GA), an improved penalty-based GA, and our multi-population conflicts sorted repair genetic algorithm (MP-CS-repair GA), as well as three kinds of service composition mechanisms-with backup, without backup, and our context-aware service re-selection mechanisms. The results show that our MP-CS-repair GA and context-aware service re-selection method can reduce more extra delay while acquiring a higher global QoS for the composite service in a context sensitive environment. This context-aware service re-selection mechanism also shows some adaptability to different context change frequencies and user requirements for reducing computation cost in the self-optimizing process.

Customer Segmentation Based on Context Preference Mining for Mobile Service

An increasing web services run in mobile context. Context may influence customer potential needs and buying behaviors in some specific situation. However existent customer segmentation method do not attach importance to context factors, which weakly support the development of context-sensitive mobile service . Therefore a mobile customer segmentation method based on context is proposed and validated by a case. The further research is mentioned in the end of the paper.

VIRTUAL EYE — THE BLIND CHILD NAVIGATION MODEL USING WIRELESS SENSOR NETWORK

The visions of context-sensitive services, ubiquitous computing, and ambient intelligence have driven several aspects of wireless sensor networks research, but perhaps none more so than localization and tracking. Location of a user is one of the most fundamental types of context, and can be applied in a vast number of environments from smart homes to improved security solutions. However, accurate localization of users is not trivial, and most of the individual systems presented suffer from coverage problems. We present a system-level approach to localize and track normal and blind users on the basis of different sources of location information. The system can be applied outdoors and indoors using GPS and Zigbee as the source of location data. The overall system architecture is modular and extendible, allowing for creation of location- and context-aware services for blind child tracking with the inclusion of additional sources of localization data. Extensive performance evaluation presented for blind child navigation shows that the system is both accurate as well as scalable.

Activity recognition in the home using a hierarchal framework with object usage data

Smart environments are emerging as platforms that can be used to help recognise activities and hence provide context sensitive services and assistance, e.g. switching on the music while the person ...

A framework for context sensitive services: A knowledge discovery based approach

Advances in mobile technologies have made the collection of customers' context information feasible. Appropriate customer centric strategies that make use of customers' context data are eagerly awaited by mobile service providers. To address this need, a framework is proposed in this paper that can be used for analyzing customers' context based behavioral data to provide suitable services to customers. Six case studies of context sensitive services are discussed to illustrate how the proposed framework can be used to improve them. Furthermore, simulated experiments are conducted using customers' behavioral data including location and time and it is found that the use of context related data leads to the discovery of deeper and improved knowledge of customers' behavior.

Activity recognition in the home using a hierarchal framework with object usage data

Smart environments are emerging as platforms that can be used to help recognise activities and hence provide context sensitive services and assistance, e.g. switching on the music while the person being monitored is having an evening meal. The ability to monitor everyday activities in a smart environment is seen as a key approach for tracking functional decline among elderly people. The motivation is to allow patients with early Alzheimer's disease to have additional years of independent living before the disease reaches the latter stages (moderate and severe). This paper describes an approach to detecting the goals of the individual subjects from sensor data that are generated by objects that are used when performing everyday activities around the home. To limit intrusion into personal privacy cameras and visual surveillance equipment are not used, as the activities are monitored using simple RFID sensors. Identification of the intentions of subjects is based on interpretation of the sensor data exploiting known structures of typical behaviours.

Towards Merging PlatΩ and PGIP

The PGIP protocol is a standard, abstract interface protocol to connect theorem provers with user interfaces. Interaction in PGIP is based on ASCII-text input and a single focus point-of-control, which indicates a linear position in the input that has been checked thus far. This fits many interactive theorem provers whose interaction model stems from command-line interpreters. PlatΩ, on the other hand, is a system with a new protocol tailored to transparently integrate theorem provers into text editors like ▪ that support semi-structured XML input files and multiple foci of attention. In this paper we extend the PGIP protocol and middleware broker to support the functionalities provided by PlatΩ and beyond. More specifically, we extend PGIP (i) to support multiple foci in provers; (ii) to display semi-structured documents; (iii) to combine prover updates with user edits; (iv) to support context-sensitive service menus, and (v) to allow multiple displays. As well as supporting ▪, the extended PGIP protocol in principle can support other editors such as OpenOffice, Word 2007 and graph viewers; we hope it will also provide guidance for extending provers to handle multiple foci.

A standard‐based context sensitive service architecture for digital object dissemination

AbstractThis paper describes a context sensitive service architecture for digital object dissemination based on OpenURL and MPEG‐21 Digital Item Adaptation (DIA). This architecture entails representing service requests using the OpenURL ContextObjects and conveying the ContextObject Representations with the OpenURL Transport. The rich expressiveness of the Usage Environment Description (UED) tool defined in the MPEG‐21 DIA standard can then be incorporated into the OpenURL ContextObject by means of OpenURL extensibility mechanism, and the MPEG‐21 DIA adaptation engine can be used to construct highly customizable and adaptive context sensitive dissemination services for institutional repositories.

Context-Sensitive Service Discovery Experimental Prototype and Evaluation

The amount of different networks and services available to users today are increasing. This introduces a need for ways to locate and sort out irrelevant services in the process of discovering available services for a user. In this paper, we describe and evaluate a prototype of an automated discovery and selection system, which locates services that are relevant to a user based on his/her context and the context of the available services. The prototype is based on a multi-level, hierarchical system approach and introduces entities called User-nodes, Super-nodes, and Root-nodes. These entities separates the network into domains that handle the complex distributed service discovery, which is based on dynamically changing context information. In the prototype, a method for performing context-sensitive service discovery has been achieved. The service discovery part utilizes UPnP, which has been extended in order to increase network scalability. The experimental analysis of service discovery times, based on different scenarios is used to optimize parameter settings of the service discovery system in order to achieve short response times.