Energy Efficient Multimedia Communications in IEEE 802.11 Networks

During the last decade wireless mobile communications have progressively become part of the people’s daily lives, leading users to expect to be “alwaysbest-connected” to the Internet, regardless of their location or time of day. This is indeed motivated by the fact that wireless access networks are increasingly ubiquitous, through different types of service providers, together with an outburst of thoroughly portable devices, namely laptops, tablets, mobile phones, among others. The “anytime and anywhere” connectivity criterion raises new challenges regarding the devices’ battery lifetime management, as energy becomes the most noteworthy restriction of the end-users’ satisfaction. This wireless access context has also stimulated the development of novel multimedia applications with high network demands, although lacking in energy-aware design. Therefore, the relationship between energy consumption and the quality of the multimedia applications perceived by end-users should be carefully investigated. This dissertation addresses energy-efficient multimedia communications in the IEEE 802.11 standard, which is the most widely used wireless access technology. It advances the literature by proposing a unique empirical assessment methodology and new power-saving algorithms, always bearing in mind the end-users’ feedback and evaluating quality perception. The new EViTEQ framework proposed in this thesis, for measuring video transmission quality and energy consumption simultaneously, in an integrated way, reveals the importance of having an empirical and high-accuracy methodology to assess the trade-off between quality and energy consumption, raised by the new end-users’ requirements. Extensive evaluations conducted with the EViTEQ framework revealed its flexibility and capability to accurately report both video transmission quality and energy consumption, as well as to be employed in rigorous investigations of network interface energy consumption patterns, regardless of the wireless access technology. Following the need to enhance the trade-off between energy consumption and application quality, this thesis proposes the Optimized Power save Algorithm for continuous Media Applications (OPAMA). By using the end-users’ feedback to establish a proper trade-off between energy consumption and application performance, OPAMA aims at enhancing the energy efficiency of end-users’ devices accessing the network through IEEE 802.11. OPAMA performance has been thoroughly analyzed within different scenarios and application types, including a simulation study and a real deployment in an Android testbed. When compared with the most popular standard power-saving mechanisms defined in the IEEE 802.11 standard, the obtained results revealed OPAMA’s capability to enhance energy efficiency, while keeping end-users’ Quality of Experience within the defined bounds. Furthermore, OPAMA was optimized to enable superior energy savings in multiple station environments, resulting in a new proposal called Enhanced Power Saving Mechanism for Multiple station Environments (OPAMA-EPS4ME). The results of this thesis highlight the relevance of having a highly accurate methodology to assess energy consumption and application quality when aiming to optimize the trade-off between energy and quality. Additionally, the obtained results based both on simulation and testbed evaluations, show clear benefits from employing userdriven power-saving techniques, such as OPAMA, instead of IEEE 802.11 standard power-saving approaches.

Leveraging Trust and Privacy Concerns in Online Social Networks: an Empirical Study

Unprecedented success of Online Social Networks, such as Facebook, has been recently overshadowed by the privacy risks they imply. Weary of privacy concerns and unable to construct their identity in the desired way, users may restrict or even terminate their platform activities. Even though this means a considerable business risk for these platforms, so far there have been no studies on how to enable social network providers to address these problems. This study fills this gap by adopting a fairness perspective to analyze related measures at the disposal of the provider. In a Structural Equation Model with 237 subjects we find that ensuring interactional and procedural justice are two important strategies to support user participation on the platform.

Mobility and bandwidth prediction in virtualized LTE systems: Architecture and challenges

Long Term Evolution (LTE) represents the fourth generation (4G) technology which is capable of providing high data rates as well as support of high speed mobility. The EU FP7 Mobile Cloud Networking (MCN) project integrates the use of cloud computing concepts in LTE mobile networks in order to increase LTE's performance. In this way a shared distributed virtualized LTE mobile network is built that can optimize the utilization of virtualized computing, storage and network resources and minimize communication delays. Two important features that can be used in such a virtualized system to improve its performance are the user mobility and bandwidth prediction. This paper introduces the architecture and challenges that are associated with user mobility and bandwidth prediction approaches in virtualized LTE systems.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Safety climate and its association with office type and team involvement in primary care

OBJECTIVE To assess differences in safety climate perceptions between occupational groups and types of office organization in primary care. METHODS Primary care physicians and nurses working in outpatient offices were surveyed about safety climate. Explorative factor analysis was performed to determine the factorial structure. Differences in mean climate scores between staff groups and types of office were tested. Logistic regression analysis was conducted to determine predictors for a 'favorable' safety climate. RESULTS 630 individuals returned the survey (response rate, 50%). Differences between occupational groups were observed in the means of the 'team-based error prevention'-scale (physician 4.0 vs. nurse 3.8, P < 0.001). Medical centers scored higher compared with single-handed offices and joint practices on the 'team-based error prevention'-scale (4.3 vs. 3.8 vs. 3.9, P < 0.001) but less favorable on the 'rules and risks'-scale (3.5 vs. 3.9 vs. 3.7, P < 0.001). Characteristics on the individual and office level predicted favorable 'team-based error prevention'-scores. Physicians (OR = 0.4, P = 0.01) and less experienced staff (OR 0.52, P = 0.04) were less likely to provide favorable scores. Individuals working at medical centers were more likely to provide positive scores compared with single-handed offices (OR 3.33, P = 0.001). The largest positive effect was associated with at least monthly team meetings (OR 6.2, P < 0.001) and participation in quality circles (OR 4.49, P < 0.001). CONCLUSIONS Results indicate that frequent quality circle participation and team meetings involving all team members are effective ways to strengthen safety climate in terms of team-based strategies and activities in error prevention.

The Law of the WTO and the Communications Law of the EC : On a Path of Harmony or Discord?

This paper presents an overview of the law of the World Trade Organization (WTO) relevant to telecommunications services and correlates this body of law with the current regulatory framework for electronic communications networks and services in the European Community. The latter has been adapted to meet the challenges of technological and market developments in communications, epitomized by the processes of digitization, enhanced transport networks and convergence. The novel solutions embodied in the EC electronic communications regime, notably, a new design of the Significant Market Power mechanism, a projected withdrawal of sector specific regulation and an affirmation of the principle of technological neutrality, pose interesting questions as to the conformity of this reformed EC communications law with the WTO rules on telecommunications services and the obligations of the European Communities and their Member States. Looking beyond the WTO legal compatibility test, essential questions regarding the need for evolution of the WTO telecommunications rules are raised. The present paper contributes to the ongoing debate in that context in light of the EC experience.

Virtual Infrastructures as a Service enabling Converged Optical Networks and Data Centres

Abstract Cloud computing service emerged as an essential component of the Enterprise {IT} infrastructure. Migration towards a full range and large-scale convergence of Cloud and network services has become the current trend for addressing requirements of the Cloud environment. Our approach takes the infrastructure as a service paradigm to build converged virtual infrastructures, which allow offering tailored performance and enable multi-tenancy over a common physical infrastructure. Thanks to virtualization, new exploitation activities of the physical infrastructures may arise for both transport network and Data Centres services. This approach makes network and Data Centres’ resources dedicated to Cloud Computing to converge on the same flexible and scalable level. The work presented here is based on the automation of the virtual infrastructure provisioning service. On top of the virtual infrastructures, a coordinated operation and control of the different resources is performed with the objective of automatically tailoring connectivity services to the Cloud service dynamics. Furthermore, in order to support elasticity of the Cloud services through the optical network, dynamic re-planning features have been provided to the virtual infrastructure service, which allows scaling up or down existing virtual infrastructures to optimize resource utilisation and dynamically adapt to users’ demands. Thus, the dynamic re-planning of the service becomes key component for the coordination of Cloud and optical network resource in an optimal way in terms of resource utilisation. The presented work is complemented with a use case of the virtual infrastructure service being adopted in a distributed Enterprise Information System, that scales up and down as a function of the application requests.

Combining Wireless Sensor Networks and Machine Learning for Flash Flood Nowcasting

This paper addresses an investigation with machine learning (ML) classification techniques to assist in the problem of flash flood now casting. We have been attempting to build a Wireless Sensor Network (WSN) to collect measurements from a river located in an urban area. The machine learning classification methods were investigated with the aim of allowing flash flood now casting, which in turn allows the WSN to give alerts to the local population. We have evaluated several types of ML taking account of the different now casting stages (i.e. Number of future time steps to forecast). We have also evaluated different data representation to be used as input of the ML techniques. The results show that different data representation can lead to results significantly better for different stages of now casting.