Formal Specification of CA-UCON model using CCA

A Context-Aware Usage CONtrol (CAUCON) model is an extension of the traditional UCON model which enables adaptation to environmental changes in the aim of preserving continuity of usage in a pervasive computing system. When the authorisations and obligations requirements are met by the subject and the object, and the conditions requirements fail due to changes in the environment or the system context, CAUCON model triggers specific actions to adapt to the new situation. Besides the data protection, CA-UCON model so enhances the quality of services, striving to keep explicit interactions with the user at a minimum. This paper proposes a formal specification of the CA-UCON model in the Calculus of Context-aware Ambients (CCA in short). This enables formal analysis of the CA-UCON model using the execution environment of CCA. For illustration, some properties of the CA-UCON model are validated for a ubiquitous learning system

Enforcement of CA-UCON Model

A Context-Aware Usage CONtrol (CA- UCON) model is an extension of the traditional UCON model which enable adaptation to environmental changes in the aim of preserving continuity of access. When the authorisations and obligations requirements are met by the subject and the object, and the conditions requirements fail due to changes in the environment or the system con- text, CA-UCON model triggers specific actions to adapt to the new situation. Besides the data protection, CA-UCON model so enhances the quality of services, striving to keep explicit interactions with the user at a minimum. In this paper, we propose an architecture of the reference monitor for the CA-UCON model and investigate a variety of enforcement approaches in ubiquitous computing systems; whether centralised, distributed or hybrid; depending on applications

Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions

Context-Aware and Adaptive Usage Control Model

Information protection is a key issue for the acceptance and adoption of pervasive computing systems where various portable devices such as smart phones, Personal Digital Assistants (PDAs) and laptop computers are being used to share information and to access digital resources via wireless connection to the Internet. Because these are resources constrained devices and highly mobile, changes in the environmental context or device context can affect the security of the system a great deal. A proper security mechanism must be put in place which is able to cope with changing environmental and system context. Usage CONtrol (UCON) model is the latest major enhancement of the traditional access control models which enables mutability of subject and object attributes, and continuity of control on usage of resources. In UCON, access permission decision is based on three factors: authorisations, obligations and conditions. While authorisations and obligations are requirements that must be fulfilled by the subject and the object, conditions are subject and object independent requirements that must be satisfied by the environment. As a consequence, access permission may be revoked (and the access stopped) as a result of changes in the environment regardless of whether the authorisations and obligations requirements are met. This constitutes a major shortcoming of the UCON model in pervasive computing systems which constantly strive to adapt to environmental changes so as to minimise disruptions to the user. We propose a Context-Aware and Adaptive Usage Control (CA-UCON) model which extends the traditional UCON model to enable adaptation to environmental changes in the aim of preserving continuity of access. Indeed, when the authorisation and obligations requirements are fulfilled by the subject and object, and the conditions requirements fail due to changes in the environmental or the system context, our proposed model CA-UCON triggers specific actions in order to adapt to the new situation, so as to ensure continuity of usage. We then propose an architecture of CA-UCON model, presenting its various components. In this model, we integrated the adaptation decision with usage decision architecture, the comprehensive definition of each components and reveals the functions performed by each components in the architecture are presented. We also propose a novel computational model of our CA-UCON architecture. This model is formally specified as a finite state machine. It demonstrates how the access request of the subject is handled in CA-UCON model, including detail with regards to revoking of access and actions undertaken due to context changes. The extension of the original UCON architecture can be understood from this model. The formal specification of the CA-UCON is presented utilising the Calculus of Context-aware Ambients (CCA). This mathematical notation is considered suitable for modelling mobile and context-aware systems and has been preferred over alternatives for the following reasons: (i) Mobility and Context awareness are primitive constructs in CCA; (ii) A system's properties can be formally analysed; (iii) Most importantly, CCA specifications are executable allowing early validation of system properties and accelerated development of prototypes. For evaluation of CA-UCON model, a real-world case study of a ubiquitous learning (u-learning) system is selected. We propose a CA-UCON model for the u-learning system. This model is then formalised in CCA and the resultant specification is executed and analysed using an execution environment of CCA. Finally, we investigate the enforcement approaches for CA-UCON model. We present the CA-UCON reference monitor architecture with its components. We then proceed to demonstrate three types of enforcement architectures of the CA-UCON model: centralised architecture, distributed architecture and hybrid architecture. These are discussed in detail, including the analysis of their merits and drawbacks

The home-forwarding mechanism to reduce the cache coherence overhead in next-generation CMPs

On the road to computer systems able to support the requirements of exascale applications, Chip Multi-Processors (CMPs) are equipped with an ever increasing number of cores interconnected through fast on-chip networks. To exploit such new architectures, the parallel software must be able to scale almost linearly with the number of cores available. To this end, the overhead introduced by the run-time system of parallel programming frameworks and by the architecture itself must be small enough in order to enable high scalability also for very fine-grained parallel programs. An approach to reduce this overhead is to use non-conventional architectural mechanisms revealing useful when certain concurrency patterns in the running application are statically or dynamically recognized. Following this idea, this paper proposes a run-time support able to reduce the effective latency of inter-thread cooperation primitives by lowering the contention on individual caches. To achieve this goal, the new home-forwarding hardware mechanism is proposed and used by our runtime in order to reduce the amount of cache-to-cache interactions generated by the cache coherence protocol. Our ideas have been emulated on the Tilera TILEPro64 CMP, showing a significant speedup improvement in some first benchmarks

A Game-Theoretic Approach for Elastic Distributed Data Stream Processing

Distributed data stream processing applications are structured as graphs of interconnected modules able to ingest high-speed data and to transform them in order to generate results of interest. Elasticity is one of the most appealing features of stream processing applications. It makes it possible to scale up/down the allocated computing resources on demand in response to fluctuations of the workload. On clouds, this represents a necessary feature to keep the operating cost at affordable levels while accommodating user-defined QoS requirements. In this article, we study this problem from a game-theoretic perspective. The control logic driving elasticity is distributed among local control agents capable of choosing the right amount of resources to use by each module. In a first step, we model the problem as a noncooperative game in which agents pursue their self-interest. We identify the Nash equilibria and we design a distributed procedure to reach the best equilibrium in the Pareto sense. As a second step, we extend the noncooperative formulation with a decentralized incentive-based mechanism in order to promote cooperation by moving the agreement point closer to the system optimum. Simulations confirm the results of our theoretical analysis and the quality of our strategies

Directional Routing Techniques in VANET

Vehicle Ad hoc Networks (VANET) emerged as a subset of the Mobile Ad hoc Network (MANET) application; it is considered to be a substantial approach to the ITS (Intelligent Transportation System). VANETs were introduced to support drivers and improve safety issues and driving comfort, as a step towards constructing a safer, cleaner and more intelligent environment. At the present time vehicles are equipped with a number of sensors and devices, including On Board Units (OBU); this enables vehicles to sense situations affecting other vehicles and manage communications, by exploiting infrastructures such as the Road Side Unit (RSU); creating a Vehicle to Infrastructure (V2I) pathway, or interacting directly with other vehicles creating a Vehicle to Vehicle (V2V) pathway. Owing to the lack of infrastructures and difficulties involved in providing comprehensive coverage for all roads because of the high expense associated with installation, the investigation in this research concentrates on the V2V communication type rather than theV2I communication type. Many challenges have emerged in VANET, encouraging researchers to investigate their research in an attempt to meet these challenges. Routing protocol issues are considered to be a critical dilemma that needs to be tackled in VANET, particularly in a sparse environment, by designing an effcient routing mechanism that impacts on enhancing network performance in terms of disseminating messages to a desireddestination, balancing the generated packet (overhead) on the network and increasing the ratio of packet delivery with a reduced time delay. VANET has some unique characteristics compared to MANET; specifically it includes high mobility and constrained patterns restricted by roads, which lead to generation of a disconnected area occurring continuously between vehicles creating a Delay Tolerant Network (DTN). This is in opposition to applying the multi-hope technique properly to deliver the packet to its desire destination. The aim in this thesis comprises two main contributions. First developing novel routing protocols for a sparse environment in VANET with the context of utilising the mobility feature, with the aid of the equipped devices, such as Global Position System (GPS) and Navigation System (NS). This approach exploits the knowledge of Second Heading Direction (SHD), which represents the knowledge of the next road direction the vehicle is intending to take, in order to increase the packet delivery ratio, and to increase the route stability by decreasing instances of route breakage. This approach comprises two approaches; the first approach was designed for a highway scenario, by selecting the next hop node based on a filtration process, to forward the packet to the desired destination, while the second approach was developed for the intersection and roundabout scenario, in order to deliver the packet to the destination (unknown location). The formalising and specification of the VSHDRP has been performed using the CCA (Calculus of Context-aware Ambient), in order to evaluate the protocols behaviours, the protocol has been validated using the ccaPL. In addition the performance of the VSHDRP has been evaluated using the NS-2 simulator; comparing it with Greedy Perimeter Stateless Routing (GPSR) protocol, to reveal the strengths and weaknesses of the protocol. Second, developing a novel approach to broadcasting the HELLO beacon message adaptively in VANET based on the node's circumstances (direction and speed), in order to minimise the broadcasting of unnecessary HELLO beacon messages. A novel architecture has been built based on the adaptive HELLO beacon message, which clarifies how the OBU components are interacting with the connected sensors, in order to portray any changes in the vehicle's circumstances, so as to take the right decision to determine appropriate action. This architecture has been built based on the concept of a context aware system, which divides the architecture into three main phases; sensing processing and acting

Supporting lay users in privacy decisions when sharing sensitive data

The first part of the thesis focuses on assisting users in choosing their privacy settings, by using machine learning to derive the optimal set of privacy settings for the user. In contrast to other work, our approach uses context factors as well as individual factors to provide a personalized set of privacy settings. The second part consists of a set of intelligent user interfaces to assist the users throughout the complete privacy journey, from defining friend groups that allow targeted information sharing; through user interfaces for selecting information recipients, to find possible errors or unusual settings, and to refine them; up to mechanisms to gather in-situ feedback on privacy incidents, and investigating how to use these to improve a user’s privacy in the future. Our studies have shown that including tailoring the privacy settings significantly increases the correctness of the predicted privacy settings; whereas the user interfaces have been shown to significantly decrease the amount of unwanted disclosures.Insbesondere nach den jüngsten Datenschutzskandalen in sozialen Netzwerken wird der Datenschutz für Benutzer immer wichtiger. Obwohl die meisten Benutzer behaupten Wert auf Datenschutz zu legen, verhalten sie sich online allerdings völlig anders: Sie lassen die meisten Datenschutzeinstellungen der online genutzten Dienste, wie z. B. von sozialen Netzwerken oder Diensten zur Standortfreigabe, unberührt und passen sie nicht an ihre Datenschutzanforderungen an. In dieser Arbeit werde ich einen Ansatz zur Lösung dieses Problems vorstellen, der auf zwei verschiedenen Säulen basiert. Der erste Teil konzentriert sich darauf, Benutzer bei der Auswahl ihrer Datenschutzeinstellungen zu unterstützen, indem maschinelles Lernen verwendet wird, um die optimalen Datenschutzeinstellungen für den Benutzer abzuleiten. Im Gegensatz zu anderen Arbeiten verwendet unser Ansatz Kontextfaktoren sowie individuelle Faktoren, um personalisierte Datenschutzeinstellungen zu generieren. Der zweite Teil besteht aus einer Reihe intelligenter Benutzeroberflächen, die die Benutzer in verschiedene Datenschutzszenarien unterstützen. Dies beginnt bei einer Oberfläche zur Definition von Freundesgruppen, die im Anschluss genutzt werden können um einen gezielten Informationsaustausch zu ermöglichen, bspw. in sozialen Netzwerken; über Benutzeroberflächen um die Empfänger von privaten Daten auszuwählen oder mögliche Fehler oder ungewöhnliche Datenschutzeinstellungen zu finden und zu verfeinern; bis hin zu Mechanismen, um In-Situ- Feedback zu Datenschutzverletzungen zum Zeitpunkt ihrer Entstehung zu sammeln und zu untersuchen, wie diese verwendet werden können, um die Privatsphäreeinstellungen eines Benutzers anzupassen. Unsere Studien haben gezeigt, dass die Verwendung von individuellen Faktoren die Korrektheit der vorhergesagten Datenschutzeinstellungen erheblich erhöht. Es hat sich gezeigt, dass die Benutzeroberflächen die Anzahl der Fehler, insbesondere versehentliches Teilen von Daten, erheblich verringern

Konzeption und Realisierung eines mobilen Assistenten für intelligentes Zeitmanagement

Durch ein immer flexibler werdendes Arbeitsumfeld mit Gleitzeit, Arbeit im Homeoffice und Eigenverantwortung der Mitarbeiter, steigt die Notwendigkeit für intelligentes Zeitmanagement seit Jahren kontinuierlich an. Während Termine mit fester Uhrzeit problemlos in einer Kalender-Anwendung erfasst werden können, müssen flexible Aufgaben ohne feste Uhrzeit in einer gesonderten To-do-Liste verwaltet werden. Durch die strikte Trennung der Anwendungen und die Tatsache, dass diese über keine eigene Intelligenz verfügen, ist der Anwender dazu gezwungen selbständig seinen Tag zu planen. Dies kann zu Stress, Fehlern und vergessenen Aufgaben führen. Im Rahmen dieser Arbeit wird ein Konzept für einen mobilen Assistenten zum intelligenten Zeitmanagement entworfen. Dieser vereint Kalender und To-do-Liste in einer Anwendung und schlägt dem Anwender anhand des Kontextes passende Aufgaben vor. Im Folgenden wird zunächst analysiert, welche Kontextinformationen für die Anwendung relevant sind und wie diese erfasst werden können. Anschließend werden bisherige Zeitmanagementsysteme evaluiert und ein Anwendungskonzept für den Assistenten entwickelt. Dabei wird großer Wert auf ein einfaches Oberflächen- und Bedienkonzept gelegt. Schließlich wird eine modular erweiterbare Softwarearchitektur für die Anwendung entworfen und implementiert