Quality of Service for Multicasting in Content Addressable Networks

Multicasting is an efficient mechanism for one to many data dissemination. Unfortunately, IP Multicasting is not widely available to end-users today, but Application Layer Multicast (ALM), such as Content Addressable Network, helps to overcome this limitation. Our OM-QoS framework offers Quality of Service support for ALMs. We evaluated OM-QoS applied to CAN and show that we can guarantee that all multicast paths support certain QoS requirements.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

Calibrating Wireless Sensor Network Simulation Models with Real-World Experiments

This paper studies the energy-efficiency and service characteristics of a recently developed energy-efficient MAC protocol for wireless sensor networks in simulation and on a real sensor hardware testbed. This opportunity is seized to illustrate how simulation models can be verified by cross-comparing simulation results with real-world experiment results. The paper demonstrates that by careful calibration of simulation model parameters, the inevitable gap between simulation models and real-world conditions can be reduced. It concludes with guidelines for a methodology for model calibration and validation of sensor network simulation models.

Service-centric Networking Extensions

This paper discusses several issues of Service-Centric Networking (SCN) as an extension of the Information-Centric Networking (ICN) paradigm. SCN allows extended caching, where not exactly the same content as requested can be read from caches, but similar content can be used to produce the content requested, e.g., by filtering or transcoding. We discuss the issue of naming and routing for general dynamic services for both tightly coupled and decoupled ICN approaches. Challenges and solutions for service management are identified, in particular for composed services, which allow distributed in-network processing of service requests. We introduce the term Software-Defined Service-Centric Networking as an extension of Software-Defined Networking. A prototype implementation for SCN proofs its validity and feasibility and underlines its potential benefits.

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.

3G network traffic sources measurement and analysis

In this paper, we show statistical analyses of several types of traffic sources in a 3G network, namely voice, video and data sources. For each traffic source type, measurements were collected in order to, on the one hand, gain better understanding of the statistical characteristics of the sources and, on the other hand, enable forecasting traffic behaviour in the network. The latter can be used to estimate service times and quality of service parameters. The probability density function, mean, variance, mean square deviation, skewness and kurtosis of the interarrival times are estimated by Wolfram Mathematica and Crystal Ball statistical tools. Based on evaluation of packet interarrival times, we show how the gamma distribution can be used in network simulations and in evaluation of available capacity in opportunistic systems. As a result, from our analyses, shape and scale parameters of gamma distribution are generated. Data can be applied also in dynamic network configuration in order to avoid potential network congestions or overflows. Copyright © 2013 John Wiley & Sons, Ltd.

Potentially avoidable 30-day hospital readmissions in medical patients: derivation and validation of a prediction model

IMPORTANCE Because effective interventions to reduce hospital readmissions are often expensive to implement, a score to predict potentially avoidable readmissions may help target the patients most likely to benefit. OBJECTIVE To derive and internally validate a prediction model for potentially avoidable 30-day hospital readmissions in medical patients using administrative and clinical data readily available prior to discharge. DESIGN Retrospective cohort study. SETTING Academic medical center in Boston, Massachusetts. PARTICIPANTS All patient discharges from any medical services between July 1, 2009, and June 30, 2010. MAIN OUTCOME MEASURES Potentially avoidable 30-day readmissions to 3 hospitals of the Partners HealthCare network were identified using a validated computerized algorithm based on administrative data (SQLape). A simple score was developed using multivariable logistic regression, with two-thirds of the sample randomly selected as the derivation cohort and one-third as the validation cohort. RESULTS Among 10 731 eligible discharges, 2398 discharges (22.3%) were followed by a 30-day readmission, of which 879 (8.5% of all discharges) were identified as potentially avoidable. The prediction score identified 7 independent factors, referred to as the HOSPITAL score: h emoglobin at discharge, discharge from an o ncology service, s odium level at discharge, p rocedure during the index admission, i ndex t ype of admission, number of a dmissions during the last 12 months, and l ength of stay. In the validation set, 26.7% of the patients were classified as high risk, with an estimated potentially avoidable readmission risk of 18.0% (observed, 18.2%). The HOSPITAL score had fair discriminatory power (C statistic, 0.71) and had good calibration. CONCLUSIONS AND RELEVANCE This simple prediction model identifies before discharge the risk of potentially avoidable 30-day readmission in medical patients. This score has potential to easily identify patients who may need more intensive transitional care interventions.

Investigation of the Network Construction Behaviour on Social Networking Sites

By enabling connections between individuals, Social Networking Sites, such as Facebook, promise to create significant individual as well as social value. Encouraging connections between users is also crucial for service providers who increasingly rely on social advertising and viral marketing campaigns as important sources of their revenue. Consequently, understanding user’s network construction behavior becomes critical. However, previous studies offer only few scattered insights into this research question. In order to fill this gap, we employ Grounded Theory methodology to derive a comprehensive model of network construction behavior on social networking sites. In the following step we assess two Structural Equation Models to gain refined insights into the motivation to send and accept friendship requests – two network expansion strategies. Based on our findings, we offer recommendations for social network providers.

Design of SOA services: experiences from industry

Because of the unknown usage scenarios, designing the elementary services of a service-oriented architecture (SOA), which form the basis for later composition, is rather difficult. Various design guide lines have been proposed by academia, tool vendors and consulting companies, but they differ in the rigor of validation and are often biased toward some technology. For that reason a multiple-case study was conducted in five large organizations that successfully introduced SOA in their daily business. The observed approaches are contrasted with the findings from a literature review to derive some recommendations for SOA service design.

Comparative effectiveness of long term drug treatment strategies to prevent asthma exacerbations: network meta-analysis

Objective To determine the comparative effectiveness and safety of current maintenance strategies in preventing exacerbations of asthma. Design Systematic review and network meta-analysis using Bayesian statistics. Data sources Cochrane systematic reviews on chronic asthma, complemented by an updated search when appropriate. Eligibility criteria Trials of adults with asthma randomised to maintenance treatments of at least 24 weeks duration and that reported on asthma exacerbations in full text. Low dose inhaled corticosteroid treatment was the comparator strategy. The primary effectiveness outcome was the rate of severe exacerbations. The secondary outcome was the composite of moderate or severe exacerbations. The rate of withdrawal was analysed as a safety outcome. Results 64 trials with 59 622 patient years of follow-up comparing 15 strategies and placebo were included. For prevention of severe exacerbations, combined inhaled corticosteroids and long acting β agonists as maintenance and reliever treatment and combined inhaled corticosteroids and long acting β agonists in a fixed daily dose performed equally well and were ranked first for effectiveness. The rate ratios compared with low dose inhaled corticosteroids were 0.44 (95% credible interval 0.29 to 0.66) and 0.51 (0.35 to 0.77), respectively. Other combined strategies were not superior to inhaled corticosteroids and all single drug treatments were inferior to single low dose inhaled corticosteroids. Safety was best for conventional best (guideline based) practice and combined maintenance and reliever therapy. Conclusions Strategies with combined inhaled corticosteroids and long acting β agonists are most effective and safe in preventing severe exacerbations of asthma, although some heterogeneity was observed in this network meta-analysis of full text reports.

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.

Revascularisation versus medical treatment in patients with stable coronary artery disease: network meta-analysis

OBJECTIVE To investigate whether revascularisation improves prognosis compared with medical treatment among patients with stable coronary artery disease. DESIGN Bayesian network meta-analyses to combine direct within trial comparisons between treatments with indirect evidence from other trials while maintaining randomisation. ELIGIBILITY CRITERIA FOR SELECTING STUDIES A strategy of initial medical treatment compared with revascularisation by coronary artery bypass grafting or Food and Drug Administration approved techniques for percutaneous revascularization: balloon angioplasty, bare metal stent, early generation paclitaxel eluting stent, sirolimus eluting stent, and zotarolimus eluting (Endeavor) stent, and new generation everolimus eluting stent, and zotarolimus eluting (Resolute) stent among patients with stable coronary artery disease. DATA SOURCES Medline and Embase from 1980 to 2013 for randomised trials comparing medical treatment with revascularisation. MAIN OUTCOME MEASURE All cause mortality. RESULTS 100 trials in 93 553 patients with 262 090 patient years of follow-up were included. Coronary artery bypass grafting was associated with a survival benefit (rate ratio 0.80, 95% credibility interval 0.70 to 0.91) compared with medical treatment. New generation drug eluting stents (everolimus: 0.75, 0.59 to 0.96; zotarolimus (Resolute): 0.65, 0.42 to 1.00) but not balloon angioplasty (0.85, 0.68 to 1.04), bare metal stents (0.92, 0.79 to 1.05), or early generation drug eluting stents (paclitaxel: 0.92, 0.75 to 1.12; sirolimus: 0.91, 0.75 to 1.10; zotarolimus (Endeavor): 0.88, 0.69 to 1.10) were associated with improved survival compared with medical treatment. Coronary artery bypass grafting reduced the risk of myocardial infarction compared with medical treatment (0.79, 0.63 to 0.99), and everolimus eluting stents showed a trend towards a reduced risk of myocardial infarction (0.75, 0.55 to 1.01). The risk of subsequent revascularisation was noticeably reduced by coronary artery bypass grafting (0.16, 0.13 to 0.20) followed by new generation drug eluting stents (zotarolimus (Resolute): 0.26, 0.17 to 0.40; everolimus: 0.27, 0.21 to 0.35), early generation drug eluting stents (zotarolimus (Endeavor): 0.37, 0.28 to 0.50; sirolimus: 0.29, 0.24 to 0.36; paclitaxel: 0.44, 0.35 to 0.54), and bare metal stents (0.69, 0.59 to 0.81) compared with medical treatment. CONCLUSION Among patients with stable coronary artery disease, coronary artery bypass grafting reduces the risk of death, myocardial infarction, and subsequent revascularisation compared with medical treatment. All stent based coronary revascularisation technologies reduce the need for revascularisation to a variable degree. Our results provide evidence for improved survival with new generation drug eluting stents but no other percutaneous revascularisation technology compared with medical treatment.

Public service motivation and performance: a critical perspective

Purpose – A growing body of literature points to the importance of public service motivation (PSM) for the performance of public organizations. The purpose of this paper is to assess the method predominantly used for studying this linkage by comparing the findings it yields without and with a correction suggested by Brewer (2006), which removes the common-method bias arising from employee-specific response tendencies. Design/methodology/approach – First, the authors conduct a systematic review of published empirical research on the effects of PSM on performance and show that all studies found have been conducted at the individual level. Performance indicators in all but three studies were obtained by surveying the same employees who were also asked about their PSM. Second, the authors conduct an empirical analysis. Using survey data from 240 organizational units within the Swiss federal government, the paper compares results from an individual-level analysis (comparable to existing research) to two analyses where the data are aggregated to the organizational level, one without and one with the correction for common-method bias suggested by Brewer (2006). Findings – Looking at the Attraction to Policy-Making dimension of PSM, there is an interesting contrast: While this variable is positively correlated with performance in both the individual-level analysis and the aggregated data analysis without the correction for common-method bias, it is not statistically associated with performance in the aggregated data analysis with the correction. Originality/value – The analysis is the first to assess the robustness of the performance-PSM linkage to a correction for common-method bias. The findings place the validity of at least one part of the individual-level linkage between PSM and performance into question.