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.

Cross-Layer Optimizations for Multimedia Distribution over Wireless Multimedia Sensor Networks and Flying Ad-Hoc Networks with Quality of Experience Support

The proliferation of multimedia content and the demand for new audio or video services have fostered the development of a new era based on multimedia information, which allowed the evolution of Wireless Multimedia Sensor Networks (WMSNs) and also Flying Ad-Hoc Networks (FANETs). In this way, live multimedia services require real-time video transmissions with a low frame loss rate, tolerable end-to-end delay, and jitter to support video dissemination with Quality of Experience (QoE) support. Hence, a key principle in a QoE-aware approach is the transmission of high priority frames (protect them) with a minimum packet loss ratio, as well as network overhead. Moreover, multimedia content must be transmitted from a given source to the destination via intermediate nodes with high reliability in a large scale scenario. The routing service must cope with dynamic topologies caused by node failure or mobility, as well as wireless channel changes, in order to continue to operate despite dynamic topologies during multimedia transmission. Finally, understanding user satisfaction on watching a video sequence is becoming a key requirement for delivery of multimedia content with QoE support. With this goal in mind, solutions involving multimedia transmissions must take into account the video characteristics to improve video quality delivery. The main research contributions of this thesis are driven by the research question how to provide multimedia distribution with high energy-efficiency, reliability, robustness, scalability, and QoE support over wireless ad hoc networks. The thesis addresses several problem domains with contributions on different layers of the communication stack. At the application layer, we introduce a QoE-aware packet redundancy mechanism to reduce the impact of the unreliable and lossy nature of wireless environment to disseminate live multimedia content. At the network layer, we introduce two routing protocols, namely video-aware Multi-hop and multi-path hierarchical routing protocol for Efficient VIdeo transmission for static WMSN scenarios (MEVI), and cross-layer link quality and geographical-aware beaconless OR protocol for multimedia FANET scenarios (XLinGO). Both protocols enable multimedia dissemination with energy-efficiency, reliability and QoE support. This is achieved by combining multiple cross-layer metrics for routing decision in order to establish reliable routes.

Gender, Professional Networks, and Subjective Career Success within Early Academic Science Careers: The Role of Gender Composition in Inside and Outside Departmental Support Networks

The present study analyzed (a) gender differences in the gender composition (i.e., the proportion of male to female contacts) of professional support networks inside and outside an individual’s academic department and (b) how these differences in gender composition relate to subjective career success (i.e., perceived career success and perceived external marketability). Results showed that the networks’ gender composition is associated with subjective career success. Men’s networks consist of a higher proportion of male to female supporters, which, in turn, was positively related to subjective career success. Additional analyses revealed that the findings could not be accounted for by alternative factors, such as network size, networking behaviors, and career ambition.

Neural representation and clinically relevant moderators of individualised self-criticism in healthy subjects

Many people routinely criticise themselves. While self-criticism is largely unproblematic for most individuals, depressed patients exhibit excessive self-critical thinking, which leads to strong negative affects. We used functional magnetic resonance imaging in healthy subjects (N = 20) to investigate neural correlates and possible psychological moderators of self-critical processing. Stimuli consisted of individually selected adjectives of personally negative content and were contrasted with neutral and negative non-self-referential adjectives. We found that confrontation with self-critical material yielded neural activity in regions involved in emotions (anterior insula/hippocampus-amygdala formation) and in anterior and posterior cortical midline structures, which are associated with self-referential and autobiographical memory processing. Furthermore, contrasts revealed an extended network of bilateral frontal brain areas. We suggest that the co-activation of superior and inferior lateral frontal brain regions reflects the recruitment of a frontal top-down pathway, representing cognitive reappraisal strategies for dealing with evoked negative affects. In addition, activation of right superior frontal areas was positively associated with neuroticism and negatively associated with cognitive reappraisal. Although these findings may not be specific to negative stimuli, they support a role for clinically relevant personality traits in successful regulation of emotion during confrontation with self-critical material.

Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes

We use a novel dataset and research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the same block are more likely to work together than individuals in nearby but not identical blocks. We find significant evidence of social interactions operating at the block level: residing on the same versus nearby blocks increases the probability of working together by over 33 percent. The results also indicate that this referral effect is stronger when individuals are similar in sociodemographic characteristics (e.g., both have children of similar ages) and when at least one individual is well attached to the labor market. These findings are robust across various specifications intended to address concerns related to sorting and reverse causation. Further, having determined the characteristics of a pair of individuals that lead to an especially strong referral effect, we provide evidence that the increased availability of neighborhood referrals has a significant impact on a wide range of labor market outcomes including employment and wages.

Production Networks and Spatial Economic Interdependence: An International Input-Output Analysis of the Asia-Pacific Region

The Asia-Pacific Region has enjoyed remarkable economic growth in the last three decades. This rapid economic growth can be partially attributed to the global spread of production networks, which has brought about major changes in spatial interdependence among economies within the region. By applying an Input-Output based spatial decomposition technique to the Asian International Input-Output Tables for 1985 and 2000, this paper not only analyzes the intrinsic mechanism of spatial economic interdependence, but also shows how value added, employment and CO2 emissions induced are distributed within the international production networks.

Optimal design of AC EMI filters with damping networks and effect on the systems power factor

The cutoff frequencies of an EMI filter are normally given by the noise attenuation requirements the filter has to fulfill. In order to select the component values of the filter elements, i.e. inductances and capacitances, an additional design criterium is needed. In this paper the effect of the EMI filter input and output impedances are considered. The input impedance influences the filters effect on the system displacement power factor and the output impedance plays a key role in the system stability. The effect of filter element values, the number of filter stages as well as additional damping networks are considered and a design procedure is provided. For this analysis a two-port description of the input filters employing ABCD-parameters is used.

Combining Wireless Sensor Networks and Semantic Middleware for an Internet of Things-Based Sportsman/Woman Monitoring Application.

Wireless Sensor Networks (WSNs) are spearheading the efforts taken to build and deploy systems aiming to accomplish the ultimate objectives of the Internet of Things. Due to the sensors WSNs nodes are provided with, and to their ubiquity and pervasive capabilities, these networks become extremely suitable for many applications that so-called conventional cabled or wireless networks are unable to handle. One of these still underdeveloped applications is monitoring physical parameters on a person. This is an especially interesting application regarding their age or activity, for any detected hazardous parameter can be notified not only to the monitored person as a warning, but also to any third party that may be helpful under critical circumstances, such as relatives or healthcare centers. We propose a system built to monitor a sportsman/woman during a workout session or performing a sport-related indoor activity. Sensors have been deployed by means of several nodes acting as the nodes of a WSN, along with a semantic middleware development used for hardware complexity abstraction purposes. The data extracted from the environment, combined with the information obtained from the user, will compose the basis of the services that can be obtained.