When scientists are looking for information in document collections, they generally have a precise objective in mind. They try to answer specific needs such as finding the definition of a concept, checking whether an idea has already been tested, or comparing the scientific conclusions of several documents. To build better information system model it is important to understand the needs of scientists in terms of information and their seeking information behaviour. The contributions of this thesis are to a) offer a user model; b) propose a generic annotation model (SciAnnotDoc) for scientific documents; c) demonstrate that the annotation model is realistic enough to be used by both manual and automatic methods of annotation; d) build a faceted search interface (FSAD) and e) evaluate the model with scientists and show that the FSAD interface is more effective than a keywords-search, notably in terms of user preference, recall and F1 measure.
In cloud computing, service resources are distributed. Cloud service markets respond simultaneously to multiple, remote customers. Every customer needs to agree with a service level agreement (SLA) to lease a new service. SLAs represent contractual terms and conditions between service providers and customers. SLA information can be complex due to the diversity and plethora of offered cloud services. Cloud SLAs lack standardization, which would motivate their automated and consistent processing. We propose the systematic management of SLA information through an SLA graph data model. The SLA graph is positioned in the cloud computing setting, where services are provisioned on-demand. We analyze how flexibly the proposed SLA graph integrates data elements and relationships that are specified by diverse business domains. The SLA graph model supports the data exchange over connected environments and endorses SLA unification and standardization efforts for cloud computing services.
The main challenge for steering IS evolution is to cope with the uncertainty inherent to any IS change, while taking into consideration its complexity due to the entanglement of its multiple dimensions: regulation, information, activity and technology. We observe that i) steering IS evolution requires understanding its IS domain, ii) its impacts are difficult to predict and iii) the guidance for IS evolution steering is almost nonexistent. Consequently, the main goal of this thesis is to provide an approach to reduce uncertainty by exploiting the information available in the IS and by considering its multiple dimensions. In particular, we intend to reach four interrelated sub-goals: 1) to propose a steering information kernel which integrates the multiple IS dimensions into one model, 2) to provide a generic model of IS evolution, 3) to provide analysis perspectives for the evolution and 4) to provide guidance for IS evolution steering.
In recent years, Wi-Fi technologies have become very popular and the trend is continuing to climb. Unfortunately, there is a risk to use Wi-Fi networks in range because there is no way to select trustworthy Wi-Fi networks. In this thesis, we focus on ways that can help users to choose the best Wi-Fi network for their needs. In order to help the user to choose the best network, our solution allows the users to rate the networks that they have used. It also checks that their assessments reflect the true network quality that they have experienced by measuring and certifying the quality of service such as delay, jitter and packet loss. The measuring process follows an innovative protocol that certifies the measurement in all cases but one. We mitigate this remaining case thanks to trust and reputation management.
This thesis proposes a new type of information, called hovering information, which is stored in geographical regions and does not rely on any infrastructure but on the mobile devices that populate the respective geographical region, its anchor area. A storage and two retrieval algorithms are proposed. They take advantage of the broadcasting nature of mobile ad hoc networks while controlling the network overhead thanks to a novel mechanism. Further, this thesis studies the persistence, accessibility, critical mass of density of nodes, the messages complexity as well as the resilience to failure of the algorithms. It also proposes a middleware and its respective implementation as an Android service which enables mobile applications to store and retrieve information from geographical regions.
A key concern in the Internet of Things (IoT) has been the integration of mundane objects in the Internet. Although increasingly interconnected, the IoT ecosystem is largely industry-centered. This leads to the creation of limited and incompatible services disempowering users by hampering their participation. In this thesis, we address this issue by empowering users to create, personalize, and distribute services in the IoT ecosystem. We define a general framework for user empowerment relying on the concepts of People, Places, Things and Applications and study their interactions. These concepts are used as design elements to implement an IoT Service Platform. The general framework, the reference implementation and the evaluation provide the design guidelines for building IoT service platforms enabling user empowerment in the IoT.
Scientists, when they read, chain document together. They reuse those chains for understanding a problem, for advancing in their research, or for writing. Systems such as Google Scholar, PubMed, Web of Knowledge, use references contained into scientific documents to link those documents together, but they are using only direct citation. More explicitly, document "a" will refer to document "b" and document "b" might refer to document "c” and those systems will create a link between these documents. But in this case “a” has a connection with “c”, but it is not explicit, therefore those systems cannot create the link. Moreover, the links between documents are not classified by type, they are generic. Users cannot know whether “a” disagree or agree with “b” without reading the document.
Emerging healthcare applications rely on personal mobile devices to monitor patient vital signs and to send it to the hospitals-backend servers for further analysis. However, these devices have limited resources that must be used optimally in order to meet the requirements of healthcare applications end-users: healthcare professionals and their patients. This paper reports on a case study of a cardiac telemonitoring application delivered by the so-called MobiHealth system. This system relies on a commercial device with multiple (wireless) network interfaces (NI). Our study focuses on how the choice of a NI affects the end-to-end applicationpsilas data delay (extremely important in case of patientpsilas emergency) and the energy consumption of the device (relating to the service sustainability while a patient is mobile). Our results show the trade-off between the delay and battery savings achieved by various NI activation strategies in combination with application-data flow adaptation. For a given mobile device, our study shows a gain of 40-90% in battery savings, traded against the higher delays (therefore applicable mainly in non-emergency cases). The insights of our studies can be used for application-data flow adaptation aiming at battery saving and prolonging devicepsilas operation for mobile patients.
Mobile service providers (MoSPs) emerge, propelled by ubiquitous availability of mobile devices and wireless communication infrastructures. MoSPs' customers satisfaction and consequently their revenues, largely depend on the quality of service (QoS) offered by wireless network providers (WNPs) at a particular location and time of a mobile service usage. This chapter presents a novel business method for the MoSP's QoS-assurance process. The method incorporates a location- and time-based QoS-predictions service facilitating the improvement of the WNP's selection process. We introduce and analyse business viability of QoSIS.net, an enterprise that provides the QoS-predictions service to MoSPs or directly to its customers (i.e. in B2B or B2C settings). QoSIS.net provides highly accurate QoS-predictions based on collaborative-sharing of QoS-information by its users. We argue that this business method can improve the MoSP's QoS-assurance process and consequently may increase its revenues, while creating revenues for QoSIS.net.
The experimental setting of Human Mobile Computer Interaction (HCI) studies is moving from the controlled laboratory to the user's daily-life environments, while employing the users' own smartphones. These studies are challenging for both new and expert researchers in human subject studies in the HCI field. Within the last three years, we conducted three different smartphone- based user studies. From these studies, we have derived key challenges that we successfully overcame during their execution. In this paper, we present the outcomes and explain the adopted solutions for the challenges identified in the design, development and execution, and data analysis phases during the user studies. Our goal is to give newcomers and junior researchers a practical view on our conducted studies, and help practitioners to reflect on their own studies and possibly apply the proposed solutions.
