Rate and predictors of service disengagement in an epidemiological first-episode psychosis cohort

To assess the prevalence and predictors of service disengagement in a treated epidemiological cohort of first-episode psychosis (FEP) patients.

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.

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.

Service Descriptions and Linked Data for Integrating WSNs into Enterprise IT

This paper presents our ongoing work on enterprise IT integration of sensor networks based on the idea of service descriptions and applying linked data principles to them. We argue that using linked service descriptions facilitates a better integration of sensor nodes into enterprise IT systems and allows SOA principles to be used within the enterprise IT and within the sensor network itself.

[Swiss Research Agenda for Nursing (SRAN): the development of an agenda for clinical nursing research in Switzerland]

In many Anglo-Saxon and North European countries nursing research agendas have been developed to address priorities in nursing research in accordance with a nationally defined health policy. In Switzerland, due to lack of a nationwide governmental health policy, co-ordination of nursing research so far was scarce. The "Swiss Research Agenda for Nursing (SRAN)" project developed an agenda for clinical nursing research between 2005 and 2007. Based on literature reviews, expert panels and a national survey a project team formulated an agenda which passed a consensus conference. The agenda recommends aspects that should lead research and defines seven research priorities for nursing in Switzerland for the time between 2007 and 2017. Nursing research should prioritize to investigate 1) the effectiveness of nursing interventions; 2) the influences of service adaptations in a changing health care system; 3) the phenomena in patients requiring nursing care; 4) the influence of the work environment on the quality of nursing care; 5) the functioning of family and social systems; 6) varieties of life circumstances and their integration; and 7) the implementation of ethical principles in nursing. Written in German and French, the Swiss Research Agenda for Nursing for the first time formulates priorities for nursing research in Switzerland and can be used for strategic discussions. As a next step, the development of an action plan to enhance nursing research will take place in Switzerland.

Comparison between two caller groups of a medical call centre in Switzerland

OBJECTIVES: The incidence distribution of triage advice in the medical call centre Medi24 and the pattern of service utilisation were analysed with respect to two groups of callers with different insurance schemes. Individuals having contracted insurance of the Medi24 model could use the telephone consultation service of the medical call centre Medi24 (mainly part of the mandatory basic health insurance) voluntarily and free of charge whereas individuals holding an insurance policy of the Telmed model (special contract within the mandatory basic health insurance with a premium discount ranging from 8% to 12%) were obliged to have a telephone consultation before arranging an appointment with a medical doctor. METHODS: A cross-sectional study was carried out in the medical call centre Medi24 based on all triage datasets of the Medi24 and Telmed groups collected during the one year period from July 1st 2005 to June 30th 2006. The distribution of the six different urgency levels within the two groups and their respective pattern of service utilisation was determined. In a multivariable logistic regression model the Odds Ratio for every enquiry originating from the Telmed group versus those originating from the Medi24 group was calculated. RESULTS: During a one-year period 48 388 triage requests reached the medical call centre Medi24, 56% derived from the Telmed group and 44% from the Medi24 group. Within the Medi24 group more than 25% of the individuals received self-care advice, within the Telmed group, on the other hand, only about 18% received such advice. In contrast, 27% of the Telmed triage requests but only 18% of the Medi24 triage requests resulted in the advice to make a routine appointment with a medical doctor. The probability that an individual of the Telmed group obtained the advice to go to the accident and emergency department was lower than for an individual of the Medi24 group (OR 0.77, 95% CI 0.60-0.99). Likewise, the probability of self-care advice was decreased in regard to the Medi24 group (OR 0.80, 95% CI 0.75-0.85). However, regarding the advice to make a routine appointment with a medical doctor, the Telmed group was represented more frequently than the Medi24 group (OR 1.36, 95% CI 1.28-1.44). CONCLUSION: In respect of the triage advice, the Telmed group differed significantly from the Medi24 group within all urgency levels. The differences between the two groups in respect of the advice given were still less pronounced than expected against the background of their different contract conditions and the disparate temporal pattern of utilisation. We interprete this finding with the fact that appraising the urgency of health problems appropriately seems to be very difficult for the majority of people seeking advice.

Dynamic Optimization of SLA-Based Services Scaling Rules

Current advanced cloud infrastructure management solutions allow scheduling actions for dynamically changing the number of running virtual machines (VMs). This approach, however, does not guarantee that the scheduled number of VMs will properly handle the actual user generated workload, especially if the user utilization patterns will change. We propose using a dynamically generated scaling model for the VMs containing the services of the distributed applications, which is able to react to the variations in the number of application users. We answer the following question: How to dynamically decide how many services of each type are needed in order to handle a larger workload within the same time constraints? We describe a mechanism for dynamically composing the SLAs for controlling the scaling of distributed services by combining data analysis mechanisms with application benchmarking using multiple VM configurations. Based on processing of multiple application benchmarks generated data sets we discover a set of service monitoring metrics able to predict critical Service Level Agreement (SLA) parameters. By combining this set of predictor metrics with a heuristic for selecting the appropriate scaling-out paths for the services of distributed applications, we show how SLA scaling rules can be inferred and then used for controlling the runtime scale-in and scale-out of distributed services. We validate our architecture and models by performing scaling experiments with a distributed application representative for the enterprise class of information systems. We show how dynamically generated SLAs can be successfully used for controlling the management of distributed services scaling.

Real-Time Passive Capturing of the GSM Radio

This paper addresses the problem of service development based on GSM handset signaling. The aim is to achieve this goal without the participation of the users, which requires the use of a passive GSM receiver on the uplink. Since no tool for GSM uplink capturing was available, we developed a new method that can synchronize to multiple mobile devices by simply overhearing traffic between them and the network. Our work includes the implementation of modules for signal recovery, message reconstruction and parsing. The method has been validated against a benchmark solution on GSM downlink and independently evaluated on uplink channels. Initial evaluations show up to 99% success rate in message decoding, which is a very promising result. Moreover, we conducted measurements that reveal insights on the impact of signal power on the capturing performance and investigate possible reactive measures.