Managed access dependability for critical services in wireless inter domain environment

The Information and Communications Technology (ICT) industry has through the last decades changed and still continues to affect the way people interact with each other and how they access and share information, services and applications in a global market characterized by constant change and evolution. For a networked and highly dynamic society, with consumers and market actors providing infrastructure, networks, services and applications, the mutual dependencies of failure free operations are getting more and more complex. Service Level Agreements (SLAs) between the various actors and users may be used to describe the offerings along with price schemes and promises regarding the delivered quality. However, there is no guarantee for failure free operations whatever efforts and means deployed. A system fails for a number of reasons, but automatic fault handling mechanisms and operational procedures may be used to decrease the probability for service interruptions. The global number of mobile broadband Internet subscriptions surpassed the number of broadband subscriptions over fixed technologies in 2010. The User Equipment (UE) has become a powerful device supporting a number of wireless access technologies and the always best connected opportunities have become a reality. Some services, e.g. health care, smart power grid control, surveillance/monitoring etc. called critical services in this thesis, put high requirements on service dependability. A definition of dependability is the ability to deliver services that can justifiably be trusted. For critical services, the access networks become crucial factors for achieving high dependability. A major challenge in a multi operator, multi technology wireless environment is the mobility of the user that necessitates handovers according to the physical movement. In this thesis it is proposed an approach for how to optimize the dependability for critical services in multi operator, multi technology wireless environment. This approach allows predicting the service availability and continuity at real-time. Predictions of the optimal service availability and continuity are considered crucial for critical services. To increase the dependability for critical services dual homing is proposed where the use of combinations of access points, possibly owned by different operators and using different technologies, are optimized for the specific location and movement of the user. A central part of the thesis is how to ensure the disjointedness of physical and logical resources so important for utilizing the dependability increase potential with dual homing. To address the interdependency issues between physical and logical resources, a study of Operations, Administrations, and Maintenance (OA&M) processes related to the access network of a commercial Global System for Mobile Communications (GSM)/Universal Mobile Telecommunications System (UMTS) operator was performed. The insight obtained by the study provided valuable information of the inter woven dependencies between different actors in the delivery chain of services. Based on the insight gained from the study of OA&M processes a technological neutral information model of physical and logical resources in the access networks is proposed. The model is used for service availability and continuity prediction and to unveil interdependencies between resources for the infrastructure. The model is proposed as an extension of the Media Independent Handover (MIH) framework. A field trial in a commercial network was conducted to verify the feasibility in retrieving the model related information from the operators' Operational Support Systems (OSSs) and to emulate the extension and usage of the MIH framework. In the thesis it is proposed how measurement reports from UE and signaling in networks are used to define virtual cells as part of the proposed extension of the MIH framework. Virtual cells are limited geographical areas where the radio conditions are homogeneous. Virtual cells have radio coverage from a number of access points. A Markovian model is proposed for prediction of the service continuity of a dual homed critical service, where both the infrastructure and radio links are considered. A dependability gain is obtained by choosing a global optimal sequence of access points. Great emphasizes have been on developing computational e cient techniques and near-optimal solutions considered important for being able to predict service continuity at real-time for critical services. The proposed techniques to obtain the global optimal sequence of access points may be used by handover and multi homing mechanisms/protocols for timely handover decisions and access point selections. With the proposed extension of the MIH framework a global optimal sequence of access points providing the highest reliability may be predicted at real-time

Coping with Credit Risk: Essays on defaulted bonds, asset based lending and provisioning for loan losses by financial institutions

Uncertainty is part of life as the quote of Benjamin Franklin clearly states. A distinction should be made between uncertainty and risk. Uncertainty includes all facts in life that do not have a certain outcome and cannot be measured. Risk1 is the measurable counterpart of uncertainty (Knight (2002)). This thesis is focused on risk, and more specically on credit risk. The risks companies face can be classied broadly into two types of risks, business risks and nancial risks. Business risks are the risks that are part of the core business of a company and which they use to create adde

Data-driven resiliency assessment of medical cyber-physical systems

Advances in computing, networking, and sensing technologies have resulted in the ubiquitous deployment of medical cyber-physical systems in various clinical and personalized settings. The increasing complexity and connectivity of such systems, the tight coupling between their cyber and physical components, and the inevitable involvement of human operators in supervision and control have introduced major challenges in ensuring system reliability, safety, and security. This dissertation takes a data-driven approach to resiliency assessment of medical cyber-physical systems. Driven by large-scale studies of real safety incidents involving medical devices, we develop techniques and tools for (i) deeper understanding of incident causes and measurement of their impacts, (ii) validation of system safety mechanisms in the presence of realistic hazard scenarios, and (iii) preemptive real-time detection of safety hazards to mitigate adverse impacts on patients. We present a framework for automated analysis of structured and unstructured data from public FDA databases on medical device recalls and adverse events. This framework allows characterization of the safety issues originated from computer failures in terms of fault classes, failure modes, and recovery actions. We develop an approach for constructing ontology models that enable automated extraction of safety-related features from unstructured text. The proposed ontology model is defined based on device-specific human-in-the-loop control structures in order to facilitate the systems-theoretic causality analysis of adverse events. Our large-scale analysis of FDA data shows that medical devices are often recalled because of failure to identify all potential safety hazards, use of safety mechanisms that have not been rigorously validated, and limited capability in real-time detection and automated mitigation of hazards. To address those problems, we develop a safety hazard injection framework for experimental validation of safety mechanisms in the presence of accidental failures and malicious attacks. To reduce the test space for safety validation, this framework uses systems-theoretic accident causality models in order to identify the critical locations within the system to target software fault injection. For mitigation of safety hazards at run time, we present a model-based analysis framework that estimates the consequences of control commands sent from the software to the physical system through real-time computation of the system’s dynamics, and preemptively detects if a command is unsafe before its adverse consequences manifest in the physical system. The proposed techniques are evaluated on a real-world cyber-physical system for robot-assisted minimally invasive surgery and are shown to be more effective than existing methods in identifying system vulnerabilities and deficiencies in safety mechanisms as well as in preemptive detection of safety hazards caused by malicious attacks