A survey on fault-models for QoS studies of service-oriented systems

This survey paper presents an overview of the fault-models available to the researcher who wants to parameterise system-models in order to study Quality- of-Service (QoS) properties of systems with service-oriented architecture. The concept of a system-model subsumes the whole spectrum between abstract mathematical models and testbeds based on actual implementations. Fault- models, on the other hand, are parameters to system-models. They introduce faults and disturbances into the system-model, thereby allowing the study of QoS under realistic conditions. In addition to a survey of existing fault- models, the paper also provides a discussion of available fault-classification schemes

Stochastic models for dependable services

In this paper we investigate the use of stochastic models for analysing service-oriented systems. We propose an iterative hybrid approach using system measurements, testbed observations as well as formal models to derive a quantitative model of service-based systems that allows us to evaluate the effectiveness of the restart method in such systems. In cases where one is fortunate enough as to have access to a real system for measurements the obtained data often is lacking statistical significance or knowledge of the system is not sufficient to explain the data. A testbed may then be preferable as it allows for long experiment series and provides full control of the system's configuration. In order to provide meaningful data the testbed must be equipped with fault-injection using a suitable fault-model and an appropriate load model. We fit phase-type distributions to the data obtained from the testbed in order to represent the observed data in a model that can be used e.g. as a service process in a queueing model of our service-oriented system. The queueing model may be used to analyse different restart policies, buffer size or service disciplines. Results from the model can be fed into the testbed and provide it with better fault and load models thus closing the modelling loop

Performance and Reliability Evaluation of Apache Kafka Messaging System

Streaming data is now flowing across various devices and applications around us. This type of data means any unbounded, ever growing, infinite data set which is continuously generated by all kinds of sources. Examples include sensor data transmitted among different Internet of Things (IoT) devices, user activity records collected on websites and payment requests sent from mobile devices. In many application scenarios, streaming data needs to be processed in real-time because its value can be futile over time. A variety of stream processing systems have been developed in the last decade and are evolving to address rising challenges. A typical stream processing system consists of multiple processing nodes in the topology of a DAG (directed acyclic graph). To build real-time streaming data pipelines across those nodes, message middleware technology is widely applied. As a distributed messaging system with high durability and scalability, Apache Kafka has become very popular among modern companies. It ingests streaming data from upstream applications and store the data in its distributed cluster, which provides a fault-tolerant data source for stream processors. Therefore, Kafka plays a critical role to ensure the completeness, correctness and timeliness of streaming data delivery. However, it is impossible to meet all the user requirements in real-time cases with a simple and fixed data delivery strategy. In this thesis, we address the challenge of choosing a proper configuration to guarantee both performance and reliability of Kafka for complex streaming application scenarios. We investigate the features that have an impact on the performance and reliability metrics. We propose a queueing based prediction model to predict the performance metrics, including producer throughput and packet latency of Kafka. We define two reliability metrics, the probability of message loss and the probability of message duplication. We create an ANN model to predict these metrics given unstable network metrics like network delay and packet loss rate. To collect sufficient training data we build a Docker-based Kafka testbed with a fault injection module. We use a new quality-of-service metric, timely throughput to help us choosing proper batch size in Kafka. Based on this metric, we propose a dynamic configuration method, which reactively guarantees both performance and reliability of Kafka under complex operation conditions

NetemCG – IP packet-loss injection using a continuous-time Gilbert model

Injection of IP packet loss is a versatile method for emulating real-world network conditions in performance studies. In order to reproduce realistic packet-loss patterns, stochastic fault-models are used. In this report we desribe our implementation of a Linux kernel module using a Continuous-Time Gilbert Model for packet-loss injection

Master/worker parallel discrete event simulation

The execution of parallel discrete event simulation across metacomputing infrastructures is examined. A master/worker architecture for parallel discrete event simulation is proposed providing robust executions under a dynamic set of services with system-level support for fault tolerance, semi-automated client-directed load balancing, portability across heterogeneous machines, and the ability to run codes on idle or time-sharing clients without significant interaction by users. Research questions and challenges associated with issues and limitations with the work distribution paradigm, targeted computational domain, performance metrics, and the intended class of applications to be used in this context are analyzed and discussed. A portable web services approach to master/worker parallel discrete event simulation is proposed and evaluated with subsequent optimizations to increase the efficiency of large-scale simulation execution through distributed master service design and intrinsic overhead reduction. New techniques for addressing challenges associated with optimistic parallel discrete event simulation across metacomputing such as rollbacks and message unsending with an inherently different computation paradigm utilizing master services and time windows are proposed and examined. Results indicate that a master/worker approach utilizing loosely coupled resources is a viable means for high throughput parallel discrete event simulation by enhancing existing computational capacity or providing alternate execution capability for less time-critical codes.Ph.D.Committee Chair: Fujimoto, Richard; Committee Member: Bader, David; Committee Member: Perumalla, Kalyan; Committee Member: Riley, George; Committee Member: Vuduc, Richar

Emergency Text Messaging Systems and Higher Education Campuses: Expanding Crisis Communication Theories and Best Practices

Recent public safety threats affecting college and university campuses during episodes of natural disasters and mass violence have exposed numerous challenges and opportunities in crisis and risk communication. The evacuation of college campuses during natural disasters such as Hurricane Katrina in 2005 and episodes of mass violence such as the shootings at the University of Alabama-Huntsville in 2010, among others, have revealed how even the most well-developed campus communication plans leave room for improvement during actual crisis events (Catullo, Walker, & Floyd, 2009). Through in-depth interviews (N=10) of crisis communication managers at U. S. colleges and universities, as well as document reviews of media coverage (N=36) of the events surrounding previous natural and manmade campus emergencies, the purpose of this paper is to examine how colleges and universities have integrated a relatively new communication technology, emergency text messaging, into their planned crisis communication response to disseminate emergency information to stakeholders, such as students, faculty, staff, and parents, during crises affecting their campuses. Through grounded theory, data systematically obtained and analyzed offer: (1) a running theoretical discussion using conceptual categories and their properties related to crisis communication adaptations of existing theories and models, including chaos theory, power, theory, and complexity theory, and (2) additional best practices for integrating emergency text messaging with other communication channels that can be applied in a university setting to increase the likelihood of a successful emergency response

Development and Performance Evaluation of Urban Mobility Applications and Services

L'abstract è presente nell'allegato / the abstract is in the attachmen

A Data-Analysis and Sensitivity-Optimization Framework for the KATRIN Experiment

Presently under construction, the Karlsruhe TRitium Neutrino (KATRIN) experiment is the next generation tritium beta-decay experiment to perform a direct kinematical measurement of the electron neutrino mass with an unprecedented sensitivity of 200 meV (90% C.L.). This thesis describes the implementation of a consistent data analysis framework, addressing technical aspects of the data taking process and statistical challenges of a neutrino mass estimation from the beta-decay electron spectrum