Prof. Dr.-Ing. Franz J. Hauck

Prof. Hauck studierte Informatik an der Universität Erlangen-Nürnberg. Nach zwei Jahren in der Industrie promovierte und habilitierte er sich an der Universität Erlangen-Nürnberg unterbrochen von einem einjährigen Auslandsaufenthalt an der Vrije Universiteit Amsterdam. Seit 2002 lehrt und forscht er an der Universität Ulm als Professor für Verteilte Systeme am gleichnamigen Institut.

Seine Forschungsinteressen sind Middleware-Systeme für spezielle Aufgaben. Der Fokus liegt auf fehlertoleranten Serversystemen, vor allem auf State-Machine Replication (SMR).

In der Lehre vertritt Prof. Hauck die Themengebiete Betriebssysteme und Verteilte Systeme. Seine aktuellen Veranstaltungen finden Sie auf der Lehreseite des Instituts. Alle seine Lehrveranstaltungen finden sich auf einer Detailseite.

Prof. Hauck ist Mitglied der ACM, der Gesellschaft für Informatik, GI und deren Fachgruppen Betriebssysteme , KuVS und FERS sowie von EuroSys.

Er ist außerdem gewähltes Mitglied des Fakultätsrats seiner Fakultät, bestelltes Mitglied der Informatik für die Gemeinsame Kommission Lehramt und damit gleichzeitig Mitglied in der Studienkommission, dem Prüfungsausschuss und dem Zulassungsausschuss für das Lehramt. Im Prüfungsausschuss Lehramt ist er gewählter Vorsitzender.

Seine letzten Publikationen:

Köstler, J., Reiser, H.P., Hauck, F.J. and Habiger, G. 2023. Fluidity: location-awareness in replicated state machines. 38th ACM/SIGAPP Symp. on Appl. Comp. – SAC (Mar. 2023). [accepted for publication]

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.

Heß, A. and Hauck, F.J. 2023. Towards a Cloud Service for State-Machine Replication. Tagungsband des FG-BS Frühjahrstreffens 2023 (Bonn - Germany, 2023).

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.

Berger, C., Reiser, H.P., Hauck, F.J., Held, F. and Domaschka, J. 2022. Automatic integration of BFT state-machine replication into IoT systems. 18th Eur. Dep. Comp. Conf. – EDCC (2022), 1–8.

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.

Berger, C., Reiser, H.P., Hauck, F.J., Held, F. and Domaschka, J. 2022. Automatic integration of BFT state-machine replication into IoT systems. CoRR. abs/2207.00500, (2022).

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.

Berger, C., Eichhammer, P., Reiser, H.P., Domaschka, J., Hauck, F.J. and Habiger, G. 2022. A survey on resilience in the IoT: taxonomy, classification, and discussion of resilience mechanisms. ACM Comp. Surv. 54, 7 (2022), 147:1-147:39.

Internet-of-Things (IoT) ecosystems tend to grow both in scale and complexity, as they consist of a variety of heterogeneous devices that span over multiple architectural IoT layers (e.g., cloud, edge, sensors). Further, IoT systems increasingly demand the resilient operability of services, as they become part of critical infrastructures. This leads to a broad variety of research works that aim to increase the resilience of these systems. In this article, we create a systematization of knowledge about existing scientific efforts of making IoT systems resilient. In particular, we first discuss the taxonomy and classification of resilience and resilience mechanisms and subsequently survey state-of-the-art resilience mechanisms that have been proposed by research work and are applicable to IoT. As part of the survey, we also discuss questions that focus on the practical aspects of resilience, e.g., which constraints resilience mechanisms impose on developers when designing resilient systems by incorporating a specific mechanism into IoT systems.

Weitere Informationen finden sich auf anderen Seiten: vollständige Publikationsliste, Doktoranden. Weitere Details zu Projekten und gehaltenen Lehrveranstaltungen finden sich auf einer Detailseite.