Authentication and Authorisation Mechanisms in support of Secure Access to WMN Resources

Over the past several years, a number of design approaches in wireless mesh networks have been introduced to support the deployment of wireless mesh networks (WMNs). We introduce a novel wireless mesh architecture that supports authentication and authorisation functionalities, giving the possibility of a seamless WMN integration into the home's organization authentication and authorisation infrastructure. First, we introduce a novel authentication and authorisation mechanism for wireless mesh nodes. The mechanism is designed upon an existing federated access control approach, i.e. the AAI infrastructure that is using just the credentials at the user's home organization in a federation. Second, we demonstrate how authentication and authorisation for end users is implemented by using an existing web-based captive portal approach. Finally, we observe the difference between the two and explain in detail the process flow of authorized access to network resources in wireless mesh networks. The goal of our wireless mesh architecture is to enable easy broadband network access to researchers at remote locations, giving them additional advantage of a secure access to their measurements, irrespective of their location. It also provides an important basis for the real-life deployment of wireless mesh networks for the support of environmental research.

Decoding Delay Minimization in Inter-Session Network Coding

Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions.

NetCodCCN: a Network Coding approach for Content-Centric Networks

Content-Centric Networking (CCN) naturally supports multi-path communication, as it allows the simultaneous use of multiple interfaces (e.g. LTE and WiFi). When multiple sources and multiple clients are considered, the optimal set of distribution trees should be determined in order to optimally use all the available interfaces. This is not a trivial task, as it is a computationally intense procedure that should be done centrally. The need for central coordination can be removed by employing network coding, which also offers improved resiliency to errors and large throughput gains. In this paper, we propose NetCodCCN, a protocol for integrating network coding in CCN. In comparison to previous works proposing to enable network coding in CCN, NetCodCCN permit Interest aggregation and Interest pipelining, which reduce the data retrieval times. The experimental evaluation shows that the proposed protocol leads to significant improvements in terms of content retrieval delay compared to the original CCN. Our results demonstrate that the use of network coding adds robustness to losses and permits to exploit more efficiently the available network resources. The performance gains are verified for content retrieval in various network scenarios.

A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

A real-time video quality estimator for emerging wireless multimedia systems

Wireless Mesh Networks (WMNs) are increasingly deployed to enable thousands of users to share, create, and access live video streaming with different characteristics and content, such as video surveillance and football matches. In this context, there is a need for new mechanisms for assessing the quality level of videos because operators are seeking to control their delivery process and optimize their network resources, while increasing the user’s satisfaction. However, the development of in-service and non-intrusive Quality of Experience assessment schemes for real-time Internet videos with different complexity and motion levels, Group of Picture lengths, and characteristics, remains a significant challenge. To address this issue, this article proposes a non-intrusive parametric real-time video quality estimator, called MultiQoE that correlates wireless networks’ impairments, videos’ characteristics, and users’ perception into a predicted Mean Opinion Score. An instance of MultiQoE was implemented in WMNs and performance evaluation results demonstrate the efficiency and accuracy of MultiQoE in predicting the user’s perception of live video streaming services when compared to subjective, objective, and well-known parametric solutions.

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.

Patterns of Psychological Adaptation to Spousal Bereavement in Old Age

Background: While the negative effects of spousal bereavement on well-being are well documented in empirical research, the large individual differences in psychological adaptation are still not well understood. Objective: This contribution aims to identify patterns of psychological adaptation to spousal loss in old age and to shed light on the role of intra- and interpersonal resources and contextual factors as discriminant variables among these patterns. Methods: The data stem from a cross-sectional questionnaire study of 402 widowed individuals (228 women, 174 men) aged between 60 and 89 years (mean age 74.41 years), who lost their partner within the last 5 years, and 618 married individuals, who served as controls (312 women, 306 men; mean age 73.82 years). Results: The exploratory latent profile analysis of the well-being outcomes of depressive symptoms, hopelessness, loneliness, life satisfaction and subjective health revealed three different groups in the widowed sample: ‘resilients' (54% of the sample), ‘copers' (39%) and ‘vulnerables' (7%). The most important variables for group allocation were intrapersonal resources - psychological resilience and the Big Five personality traits - but also the quality of the former relationship and how the loss was experienced. Conclusion: Successful adaptation to spousal loss is primarily associated with high scores in psychological resilience and extraversion and low scores in neuroticism. Our results shed light on the variability in psychological adaptation and underline the important role of intrapersonal resources in facing spousal loss in old age.

Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

User and Machine Authentication and Authorization Infrastructure for Distributed Wireless Sensor Network Testbeds

The intention of an authentication and authorization infrastructure (AAI) is to simplify and unify access to different web resources. With a single login, a user can access web applications at multiple organizations. The Shibboleth authentication and authorization infrastructure is a standards-based, open source software package for web single sign-on (SSO) across or within organizational boundaries. It allows service providers to make fine-grained authorization decisions for individual access of protected online resources. The Shibboleth system is a widely used AAI, but only supports protection of browser-based web resources. We have implemented a Shibboleth AAI extension to protect web services using Simple Object Access Protocol (SOAP). Besides user authentication for browser-based web resources, this extension also provides user and machine authentication for web service-based resources. Although implemented for a Shibboleth AAI, the architecture can be easily adapted to other AAIs.

Association of lectin pathway proteins with intra-abdominal Candida infection in high-risk surgical intensive-care unit patients. A prospective cohort study within the fungal infection network of Switzerland

OBJECTIVES Human studies on the role of mannose-binding lectin (MBL) in patients with invasive candidiasis have yielded conflicting results. We investigated the influence of MBL and other lectin pathway proteins on Candida colonization and intra-abdominal candidiasis (IAC) in a cohort of high-risk patients. METHODS Prospective observational cohort study of 89 high-risk intensive-care unit (ICU) patients. Levels of lectin pathway proteins at study entry and six MBL2 single-nucleotide polymorphisms were analyzed by sandwich-type immunoassays and genotyping, respectively, and correlated with development of heavy Candida colonization (corrected colonization index (CCI) ≥0.4) and occurrence of IAC during a 4-week period. RESULTS Within 4 weeks after inclusion a CCI ≥0.4 and IAC was observed in 47% and 38% of patients respectively. Neither serum levels of MBL, ficolin-1, -2, -3, MASP-2 or collectin liver 1 nor MBL2 genotypes were associated with a CCI ≥0.4. Similarly, none of the analyzed proteins was found to be associated with IAC with the exception of lower MBL levels (HR 0.74, p = 0.02) at study entry. However, there was no association of MBL deficiency (<0.5 μg/ml), MBL2 haplo- or genotypes with IAC. CONCLUSION Lectin pathway protein levels and MBL2 genotype investigated in this study were not associated with heavy Candida colonization or IAC in a cohort of high-risk ICU patients.

Network Dynamics in Natural Resource Governance: A Case Study of Swiss Landscape Management

Structural characteristics of social networks have been recognized as important factors of effective natural resource governance. However, network analyses of natural resource governance most often remain static, even though governance is an inherently dynamic process. In this article, we investigate the evolution of a social network of organizational actors involved in the governance of natural resources in a regional nature park project in Switzerland. We ask how the maturation of a governance network affects bonding social capital and centralization in the network. Applying separable temporal exponential random graph modeling (STERGM), we test two hypotheses based on the risk hypothesis by Berardo and Scholz (2010) in a longitudinal setting. Results show that network dynamics clearly follow the expected trend toward generating bonding social capital but do not imply a shift toward less hierarchical and more decentralized structures over time. We investigate how these structural processes may contribute to network effectiveness over time.

Can outcome prediction data change patient outcomes and organizational outcomes?

PURPOSE OF REVIEW: Intensive care medicine consumes a high share of healthcare costs, and there is growing pressure to use the scarce resources efficiently. Accordingly, organizational issues and quality management have become an important focus of interest in recent years. Here, we will review current concepts of how outcome data can be used to identify areas requiring action. RECENT FINDINGS: Using recently established models of outcome assessment, wide variability between individual ICUs is found, both with respect to outcome and resource use. Such variability implies that there are large differences in patient care processes not only within the ICU but also in pre-ICU and post-ICU care. Indeed, measures to improve the patient process in the ICU (including care of the critically ill, patient safety, and management of the ICU) have been presented in a number of recently published papers. SUMMARY: Outcome assessment models provide an important framework for benchmarking. They may help the individual ICU to spot appropriate fields of action, plan and initiate quality improvement projects, and monitor the consequences of such activity.

Parameter-free extraction of the functional network topology from intracranial EEG recordings: a time-resolved study of graph properties in focal onset seizures

Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

Illegitimate tasks associated with higher cortisol levels among male employees when subjective health is relatively low: an intra-individual analysis

Objectives Illegitimate tasks refer to tasks that do not conform to what can appropriately be expected from an employee. Violating role expectations, they constitute “identity-stressors”, as one’s professional role tends to become part of one’s identity. The current study investigated the impact of illegitimate tasks on salivary cortisol. We analyzed data on an intra-individual level, that is, by examining fluctuations in illegitimate tasks and cortisol within individuals. Furthermore, we investigated the moderating role of perceived health, expecting that illegitimate tasks evoke stronger reactions when perceived health is relatively poor. Methods Illegitimate tasks, salivary cortisol, and perceived health were assessed in each of three waves (time lag: 6 months) in a sample of 104 male employees. Data were analyzed by multilevel analysis using group mean centering. Results Controlling for social stressors, work interruptions, and emotional stability, the experience of more illegitimate tasks was associated with increased cortisol release if personal health resources were low compared to one’s mean value of perceived health. Results cannot be explained by inter-individual differences. Conclusions This is the first study showing that illegitimate tasks predict a biological indicator of stress, thus confirming and extending previous research on illegitimate tasks. The moderating role of perceived health confirms its importance as a personal resource, implying augmented vulnerability when perceived health is below its usual value. It is plausible to assume that increased stress reactions due to relatively poor health may further weaken available personal resources. Both avoiding illegitimate tasks and restoring personal health seem to be crucial.