110 research outputs found
Architecture and Implementation of a Trust Model for Pervasive Applications
Collaborative effort to share resources is a significant feature of pervasive computing environments. To achieve secure service discovery and sharing, and to distinguish between malevolent and benevolent entities, trust models must be defined. It is critical to estimate a device\u27s initial trust value because of the transient nature of pervasive smart space; however, most of the prior research work on trust models for pervasive applications used the notion of constant initial trust assignment. In this paper, we design and implement a trust model called DIRT. We categorize services in different security levels and depending on the service requester\u27s context information, we calculate the initial trust value. Our trust value is assigned for each device and for each service. Our overall trust estimation for a service depends on the recommendations of the neighbouring devices, inference from other service-trust values for that device, and direct trust experience. We provide an extensive survey of related work, and we demonstrate the distinguishing features of our proposed model with respect to the existing models. We implement a healthcare-monitoring application and a location-based service prototype over DIRT. We also provide a performance analysis of the model with respect to some of its important characteristics tested in various scenarios
ERMHAN: A Context-Aware Service Platform to Support Continuous Care Networks for Home-Based Assistance
Continuous care models for chronic diseases pose several technology-oriented challenges for home-based continuous care, where assistance services rely on a close collaboration among different stakeholders such as health operators, patient relatives, and social community members. Here we describe Emilia Romagna Mobile Health Assistance Network (ERMHAN) a multichannel context-aware service platform designed to support care networks in cooperating and sharing information with the goal of improving patient quality of life. In order to meet extensibility and flexibility requirements, this platform has been developed through ontology-based context-aware computing and a service oriented approach. We also provide some preliminary results of performance analysis and user survey activity
A review of the role of sensors in mobile context-aware recommendation systems
Recommendation systems are specialized in offering suggestions about specific items of different types (e.g., books, movies, restaurants, and hotels) that could be interesting for the user. They have attracted considerable research attention due to their benefits and also their commercial interest. Particularly, in recent years, the concept of context-aware recommendation system has appeared to emphasize the importance of considering the context of the situations in which the user is involved in order to provide more accurate recommendations. The detection of the context requires the use of sensors of different types, which measure different context variables. Despite the relevant role played by sensors in the development of context-aware recommendation systems, sensors and recommendation approaches are two fields usually studied independently. In this paper, we provide a survey on the use of sensors for recommendation systems. Our contribution can be seen from a double perspective. On the one hand, we overview existing techniques used to detect context factors that could be relevant for recommendation. On the other hand, we illustrate the interest of sensors by considering different recommendation use cases and scenarios
Mechanisms for improving information quality in smartphone crowdsensing systems
Given its potential for a large variety of real-life applications, smartphone crowdsensing has recently gained tremendous attention from the research community. Smartphone crowdsensing is a paradigm that allows ordinary citizens to participate in large-scale sensing surveys by using user-friendly applications installed in their smartphones. In this way, fine-grained sensing information is obtained from smartphone users without employing fixed and expensive infrastructure, and with negligible maintenance costs.
Existing smartphone sensing systems depend completely on the participants\u27 willingness to submit up-to-date and accurate information regarding the events being monitored. Therefore, it becomes paramount to scalably and effectively determine, enforce, and optimize the information quality of the sensing reports submitted by the participants. To this end, mechanisms to improve information quality in smartphone crowdsensing systems were designed in this work. Firstly, the FIRST framework is presented, which is a reputation-based mechanism that leverages the concept of mobile trusted participants to determine and improve the information quality of collected data. Secondly, it is mathematically modeled and studied the problem of maximizing the likelihood of successful execution of sensing tasks when participants having uncertain mobility execute sensing tasks. Two incentive mechanisms based on game and auction theory are then proposed to efficiently and scalably solve such problem. Experimental results demonstrate that the mechanisms developed in this thesis outperform existing state of the art in improving information quality in smartphone crowdsensing systems --Abstract, page iii
Optical boundaries for LED-based indoor positioning system
Overlap of footprints of light emitting diodes (LEDs) increases the positioning accuracy of wearable LED indoor positioning systems (IPS) but such an approach assumes that the footprint boundaries are defined. In this work, we develop a mathematical model for defining the footprint boundaries of an LED in terms of a threshold angle instead of the conventional half or full angle. To show the effect of the threshold angle, we compare how overlaps and receiver tilts affect the performance of an LED-based IPS when the optical boundary is defined at the threshold angle and at the full angle. Using experimental measurements, simulations, and theoretical analysis, the effect of the defined threshold angle is estimated. The results show that the positional time when using the newly defined threshold angle is 12 times shorter than the time when the full angle is used. When the effect of tilt is considered, the threshold angle time is 22 times shorter than the full angle positioning time. Regarding accuracy, it is shown in this work that a positioning error as low as 230 mm can be obtained. Consequently, while the IPS gives a very low positioning error, a defined threshold angle reduces delays in an overlap-based LED IPS
A Fault-Tolerant Emergency-Aware Access Control Scheme for Cyber-Physical Systems
Access control is an issue of paramount importance in cyber-physical systems
(CPS). In this paper, an access control scheme, namely FEAC, is presented for
CPS. FEAC can not only provide the ability to control access to data in normal
situations, but also adaptively assign emergency-role and permissions to
specific subjects and inform subjects without explicit access requests to
handle emergency situations in a proactive manner. In FEAC, emergency-group and
emergency-dependency are introduced. Emergencies are processed in sequence
within the group and in parallel among groups. A priority and dependency model
called PD-AGM is used to select optimal response-action execution path aiming
to eliminate all emergencies that occurred within the system. Fault-tolerant
access control polices are used to address failure in emergency management. A
case study of the hospital medical care application shows the effectiveness of
FEAC
Nature-Inspired Coordination Models: Current Status and Future Trends
Coordination models and languages are meant to provide abstractions and mechanisms to harness the space of interaction as one of the foremost sources of complexity in computational systems. Nature-inspired computing aims at understanding the mechanisms and patterns of complex natural systems in order to bring their most desirable features to computational systems. Thus, the promise of nature-inspired coordination models is to prove themselves fundamental in the design of complex computational systems|such as intelligent, knowledge-intensive, pervasive, adaptive, and self-organising ones. In this paper, we survey the most relevant nature-inspired coordination models in the literature, focussing in particular on tuple-based models, and foresee the most interesting research trends in the field
Real-Time and Secure Wireless Health Monitoring
We present a framework for a wireless health
monitoring system using wireless networks such as ZigBee. Vital
signals are collected and processed using a 3-tiered architecture.
The first stage is the mobile device carried on the body that
runs a number of wired and wireless probes. This device is also
designed to perform some basic processing such as the heart
rate and fatal failure detection. At the second stage, further
processing is performed by a local server using the raw data
transmitted by the mobile device continuously. The raw data is
also stored at this server. The processed data as well as the
analysis results are then transmitted to the service provider
center for diagnostic reviews as well as storage. The main
advantages of the proposed framework are (1) the ability to
detect signals wirelessly within a body sensor network (BSN),
(2) low-power and reliable data transmission through ZigBee
network nodes, (3) secure transmission of medical data over BSN,
(4) efficient channel allocation for medical data transmission over
wireless networks, and (5) optimized analysis of data using an
adaptive architecture that maximizes the utility of processing and
computational capacity at each platform
Wearables for Industrial Work Safety: A Survey
Today, ensuring work safety is considered to be one of the top priorities for various industries. Workplace injuries, illnesses, and deaths often entail substantial production and financial losses, governmental checks, series of dismissals, and loss of reputation. Wearable devices are one of the technologies that flourished with the fourth industrial revolution or Industry 4.0, allowing employers to monitor and maintain safety at workplaces. The purpose of this article is to systematize knowledge in the field of industrial wearables’ safety to assess the relevance of their use in enterprises as the technology maintaining occupational safety, to correlate the benefits and costs of their implementation, and, by identifying research gaps, to outline promising directions for future work in this area. We categorize industrial wearable functions into four classes (monitoring, supporting, training, and tracking) and provide a classification of the metrics collected by wearables to better understand the potential role of wearable technology in preserving workplace safety. Furthermore, we discuss key communication technologies and localization techniques utilized in wearable-based work safety solutions. Finally, we analyze the main challenges that need to be addressed to further enable and support the use of wearable devices for industrial work safety
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