Prof. Dr.-Ing. Franz J. Hauck

In planetary-scale replication systems, the overall response delay is greatly influenced by the geographical distances between client and server nodes. Current systems define the replica locations statically during startup time. However, the selected locations might be suboptimal for the clients, and the client request origin distribution may change over time, so a different replica placement may provide lower overall request latencies. In this work, we propose a locationaware replicated state machine that is able to adapt the geographic location of its replicas dynamically during runtime to locations geographically closer to client request origins. Our prototype is able to observe emerging optimization potentials and to reduce the overall request latency for the majority of clients by adapting its replica locations to the time-dependent optimum placement during real-world use case evaluations, whereby the absolute performance gain is dependent on the respective usage scenario.

State-machine replication (SMR) is a well-known technique to achieve fault tolerance for services that require high availability and fast recovery times. While the concept of SMR has been extensively investigated, there are still missing building blocks to provide a generic offer, which automatically serves applications with SMR technology in the cloud. In this work, we introduce a cloud service architecture that enables automatic deployment of service applications based on customer-friendly service parameters, which are mapped onto an internal configuration that comprises the number of replicas, tolerable failures, and the consensus algorithm, amongst other aspects. The deployed service configuration is masked to large extent with the use of threshold signatures. As a consequence, a reconfiguration in the cloud deployment does not affect the client-side code. We conclude the paper by discussing open engineering questions that need to be addressed in order to provide a productive cloud offer.

Mit der Einführung bzw. dem Ausbau des seit Jahren geforderten Pflichtfaches Informatik entsteht noch mehr Bedarf an qualifizierten Lehrkräften. Auch wenn Maßnahmen zur Nachqualifizierung von bestehenden Lehrkräften einen wichtigen Beitrag zur Deckung des Bedarfs leisten, muss gleichzeitig die Anzahl der Absolvent:innen aus lehramtsbezogenen Informatik-Studiengängen gesteigert werden. Allerdings zeigen die Zahlen, dass es noch immer zu wenig Studienanfänger:innen und noch weniger Absolvent:innen im Lehramt Informatik gibt. Um Maßnahmen zur Stärkung der Lehramtsausbildung im Fach Informatik gezielt auszurichten, muss der Berufswahlprozess erneut in den Blick genommen werden. Die wenigen bisher dazu durchgeführten Untersuchungen haben hier verschiedene Fragen offengelassen bzw. aufgrund der noch nicht ausreichenden Datenlage teils nur mit Vermutungen beantworten können. Der vorliegende Artikel widmet sich der Auswertung einer landesweit in Baden-Württemberg durchgeführten Umfrage unter aktiven Lehramtsstudierenden der Informatik mit erfreulich hoher Rücklaufquote. Es werden neue Erkenntnisse zur Reihenfolge von Teilentscheidungen für das Lehramtsstudium bzw. für die Fächer vorgestellt und der Anteil an Fachwechsler:innen betrachtet. Es wird unterschieden zwischen Studierenden, die während der Schulzeit keinen, einen als nicht gut bewerteten oder als gut bewerteten Informatikunterricht hatten. Darüber hinaus werden Motive der Berufs- bzw. Studiengangswahl in den Blick genommen und der Frage nach Unterschieden zwischen männlichen und weiblichen Studierenden nachgegangen.

Byzantine fault tolerance (BFT) can preserve the availability and integrity of IoT systems where single components may suffer from random data corruption or attacks that can expose them to malicious behavior. While state-of-the-art BFT state-machine replication (SMR) libraries are often tailored to fit a standard request-response interaction model with dedicated client-server roles, in our design, we employ an IoT-fit interaction model that assumes a loosly-coupled, event-driven interaction between arbitrarily wired IoT components.In this paper, we explore the possibility of automating and streamlining the complete process of integrating BFT SMR into a component-based IoT execution environment. Our main goal is providing simplicity for the developer: We strive to decouple the specification of a logical application architecture from the difficulty of incorporating BFT replication mechanisms into it. Thus, our contributions address the automated configuration, rewiring and deployment of IoT components, and their replicas, within a component-based, event-driven IoT platform.

Byzantine fault tolerance (BFT) can preserve the availability and integrity of IoT systems where single components may suffer from random data corruption or attacks that can expose them to malicious behavior. While state-of-the-art BFT state-machine replication (SMR) libraries are often tailored to fit a standard request-response interaction model with dedicated client-server roles, in our design, we employ an IoT-fit interaction model that assumes a loosly-coupled, event-driven interaction between arbitrarily wired IoT components. In this paper, we explore the possibility of automating and streamlining the complete process of integrating BFT SMR into a component-based IoT execution environment. Our main goal is providing simplicity for the developer: We strive to decouple the specification of a logical application architecture from the difficulty of incorporating BFT replication mechanisms into it. Thus, our contributions address the automated configuration, re-wiring and deployment of IoT components, and their replicas, within a component-based, event-driven IoT platform.