This file was created by the TYPO3 extension publications --- Timezone: CEST Creation date: 2026-04-15 Creation time: 02:20:19 --- Number of references 16 article Koestler21a Data streaming platforms connect heterogeneous services through the publish-subscribe paradigm. Currently available platforms provide protection against crash faults, but are not resistant against Byzantine faults like arbitrary hardware faults and intrusions. State machine replication can provide this protection, but the higher resource requirements and the more elaborate communication primitives usually result in a higher overall complexity and a non-negligible performance degradation. As data streaming operates on highly-partitionable append-only state, some of these performance losses can be counteracted by applying speculative execution and sharding. We show the effectiveness of these concepts in a prototype implementation, which only results in a reasonable drop in system throughput and latency during average system utilization, when compared to state-of-the-art data streaming platforms like Apache Kafka, while providing stronger resilience guarantees. 2021 10 10.1145/3493499.3493501 SIGAPP Appl. Comput. Rev. 21 ACM

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19–32 3 replication, sharding, speculation, byzantine fault tolerance, state machine, message broker, streaming platform Johannes K\"{o}stler Hans P. Reiser Gerhard Habiger Franz J. Hauck article Koestler21a Data streaming platforms connect heterogeneous services through the publish-subscribe paradigm. Currently available platforms provide protection against crash faults, but are not resistant against Byzantine faults like arbitrary hardware faults and intrusions. State machine replication can provide this protection, but the higher resource requirements and the more elaborate communication primitives usually result in a higher overall complexity and a non-negligible performance degradation. As data streaming operates on highly-partitionable append-only state, some of these performance losses can be counteracted by applying speculative execution and sharding. We show the effectiveness of these concepts in a prototype implementation, which only results in a reasonable drop in system throughput and latency during average system utilization, when compared to state-of-the-art data streaming platforms like Apache Kafka, while providing stronger resilience guarantees. 2021 10 10.1145/3493499.3493501 SIGAPP Appl. Comput. Rev. 21 ACM

New York, NY, USA

19-32 3 replication, sharding, speculation, byzantine fault tolerance, state machine, message broker, streaming platform Johannes Köstler Hans P. Reiser Gerhard Habiger Franz J. Hauck article Berger21CSUR 2021 6 1 10.1145/3462513 ACM Comp. Surv. 54 7 SORRIR,ARTeam Christian Berger Philipp Eichhammer Hans P. Reiser Jörg Domaschka Franz J. Hauck Gerhard Habiger inproceedings Koestler21smartstream Data streaming platforms connect heterogeneous services through the publish-subscribe paradigm. Currently available platforms provide protection against crash faults, but are not resistant against Byzantine faults like arbitrary hardware faults and intrusions. State machine replication can provide this protection, but the higher resource requirements and the more elaborated communication primitives usually result in a higher overall complexity and a non-negligible performance degradation. This is especially true for data streaming if the default textbook approach of integrating the service into a replicated state machine is followed without further adaptions. The standard state management with state logs and snapshots and without any partitioning scheme limits both performance and scalability in a way those systems become unusable in practice. That is why we propose SmartStream, a topic-based Byzantine fault-tolerant data streaming platform that harmonizes the competing concepts of both systems and leverages the specific characteristics of data streaming, namely the append-only semantics of the application state and its partitionable structure. We show its effectiveness in a prototype implementation and evaluate its performance. The evaluation results show a moderate drop in system throughput when compared to state-of-the-art data streaming platforms like Apache Kafka, but reasonable overall performance considering the stronger resilience guarantees. 2021 3 10.1145/3412841.3441904 36th Ann. ACM Symp. on Appl. Comp. (SAC) ACM

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213–222 publish-subscribe, streaming platform, message broker, byzantine fault tolerance, state machine, replication Johannes Köstler Hans P. Reiser Gerhard Habiger Franz J. Hauck inproceedings RDB0817 2020 1 10.1109/SRDS51746.2020.00024 Proc. of the 39th Int. Symp. on Rel. Distr. Sys. (SRDS) ARTEAM, OptSCORE Gerhard Habiger Franz J. Hauck Hans P. Reiser Johannes Köstler inproceedings DomaschkaM4IoT2019 2019 12 1 10.1145/3366610.3368098 Proc. of 6th Int. Worksh. on Middlew. and App. for the Internet of Things (M4IoT) 13-16 Davis, CA ARTeam, SORRIR Jörg Domaschka Christian Berger Hans P. Reiser Philipp Eichhammer Frank Griesinger Jakob Pietron Matthias Tichy Franz J. Hauck Gerhard Habiger inproceedings HabigerFBSYS2019 2019 10.18420/fbsys2019-04 Tagungsband des FB-SYS Herbsttreffens 2019 GI Osnabrück ARTeam, OptSCORE Gerhard Habiger Franz J. Hauck inproceedings EichhFBSYS2019 2019 10.18420/fbsys2019-03 Tagungsband des FB-SYS Herbsttreffens 2019 GI Osnabrück ARTeam, SORRIR Philipp Eichhammer Christian Berger Hans P. Reiser Jörg Domaschka Franz J. Hauck Gerhard Habiger Frank Griesinger Jakob Pietron conference HabigerHKR2018 State-machine replication (SMR) enables transparent and delayless masking of node faults. It can tolerate crash faults and malicious misbehavior, but usually comes with high resource costs, not only by requiring multiple active replicas, but also by providing the replicas with enough resources for the expected peak load. This paper presents a vertical resource-scaling solution for SMR systems in virtualized environments, which can dynamically adapt the number of available cores to current load. In similar approaches, benefits of CPU core scaling are usually small due to the inherent sequential execution of SMR systems in order to achieve determinism. In our approach, we utilize sophisticated deterministic multithreading to avoid this bottleneck and experimentally demonstrate that core scaling then allows SMR systems to effectively tailor resources to service load, dramatically reducing service provider costs. 2018 9 1 10.1109/EDCC.2018.00024 Proc. of the 14th Eur. Dep. Comp. Conf. (EDCC) IEEE Iaşi, Romania OptSCORE, ARTeam Gerhard Habiger Franz J. Hauck Johannes Köstler Hans P. Reiser conference ErbMHPK2017 An increasing number of distributed, event-based systems adopt an architectural style called event sourcing, in which entities keep their entire history in an event log. Event sourcing enables data lineage and allows entities to rebuild any previous state. Restoring previous application states is a straightforward task in event-sourced systems with a global and totally ordered event log. However, the extraction of causally consistent snapshots from distributed, individual event logs is rendered non-trivial due to causal relationships between communicating entities. High dynamicity of entities increases the complexity of such reconstructions even more. We present approaches for retrospective and global state extraction of event-sourced applications based on distributed event logs. We provide an overview on historical approaches towards distributed debugging and breakpointing, which are closely related to event log-based state reconstruction. We then introduce and evaluate our approach for non-local state extraction from distributed event logs, which is specifically adapted for dynamic and asynchronous event-sourced systems. 2017 3 10.1109/NetSys.2017.7903947 Proc. of the Int. Conf. on Netw. Sys. (NetSys) Göttingen SIDGRAPH, ARTeam Benjamin Erb Dominik Meißner Gerhard Habiger Jakob Pietron Frank Kargl conference HauckHD2016 2016 9 1 10.1109/SRDS.2016.030 Proc. of the 35th Int. Symp. on Reliable Distrib. Sys. (SRDS) Budapest, Hungry OptSCORE, ARTeam Franz J. Hauck Gerhard Habiger Jörg Domaschka conference ErbHH2016 The actor model is an established programming model for distributed applications. Combining event sourcing with the actor model allows the reconstruction of previous states of an actor. When this event sourcing approach for actors is enhanced with additional causality information, novel types of actor-based, retroactive computations are possible. A globally consistent state of all actors can be reconstructed retrospectively. Even retroactive changes of actor behavior, state, or messaging are possible, with partial recomputations and projections of changes in the past. We believe that this approach may provide beneficial features to actor-based systems, including retroactive bugfixing of applications, decoupled asynchronous global state reconstruction for recovery, simulations, and exploration of distributed applications and algorithms. 2016 7 17 1 10.1145/2957319.2957378 Proc. of the 1st Workshop on Progr. Models and Lang. for Distrib. Comp. Rome, Italy SIDGRAPH, ARTeam Benjamin Erb Gerhard Habiger Franz J. Hauck mastersthesis Habiger2016 Current research efforts of our institute include a project on deterministic scheduling of multithreaded applications for State Machine Replication (SMR) systems with Byzantine Fault Tolerance (BFT). One part of this project aims to integrate our own work on deterministic scheduling with the BFT SMaRt library. Currently, BFT SMaRt only supports synchronous request-response patterns, whereas our planned SMR platform needs these patterns to be asynchronous. The goals of this project are (i) to analyze the existing BFT SMaRt codebase, (ii) to implement the necessary interfaces for asynchronous request handling and (iii) to integrate these changes into the existing BFT SMaRt libraries. 4 2016 Institute of Distributed Systems PROJEKT, GerhardHabiger Gerhard Habiger report HabigerHKR2016 Kurzfassung für das Herbsttreffen der GI/VDE/ITG Fachgruppe Betriebssysteme 2016 2016 OptSCORE, ARTeam https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.200/files/publikationen/Habiger16.pdf Gerhard Habiger Franz J. Hauck Johannes Köstler Hans P. Reiser mastersthesis Habiger2015 Two interesting approaches to tackle many of today's problems in large scale data processing and live query resolution on big graph datasets have emerged in recent years. Firstly, after Google's presentation of its graph computing platform Pregel in 2010, an influx of more or less similar platforms could be observed. These platforms all share the goal of providing highly performant data mining and analysis capabilities to users, enabling a wide variety of today's technologies like ranking web pages in the the web graph of the WWW or analysing user interactions in social networks. Secondly, the old concept of message logging for failure recovery was rediscovered and combined with event based computing in the early 2000s and is now known as event sourcing. This approach to system design keeps persistent logs of every single change of all entities in a computation, providing highly interesting options like state restoration by replaying old events, retroactive event modifications, phenomenal debugging capabilities and many more. A recently published paper suggests the merging of those two approaches to create a hybrid event-sourced graph computing platform. This platform would show unique characteristics compared to other known solutions. For example, computations on temporal data can yield information about the evolution of a graph and not only its current state. Furthermore, for backups or to enable offline analysis on large compute clusters, snapshot extraction – i.e. reproducing any consistent global state the graph has ever been in – from the event logs produced by event-sourced graph computations is possible. This thesis provides one of the first major works related to this proposed hybrid platform and provides background knowledge related to these aforementioned topics. It presents a thorough overview over the current state-of-the-art in graph computing platforms and causality tracking in distributed systems and finally develops an efficient mechanism for extracting arbitrary, consistent global snapshots from a distributed event log produced by an event-sourced graph computation. Masterarbeit VS-M13-2015 2015 10 Institut für Verteilte Systeme, Universität Ulm BA, AA, MA, DA, BenjaminErb, FrankKargl, sidgraph, distributed Gerhard Habiger mastersthesis Habiger2013 The high demand and growing market for Implantable Medical Devices shows a widespread need for invisible and unobtrusive medical treatment of medical conditions like e.g. diabetes or cardiac arrythmia. The advancements of technology in this field make devices increasingly inter-connected, allowing them to communicate wirelessly with sensors, medical telemetry systems or device programmers. However, the increased complexity and the fact that many medical devices nowadays can be programmed and controlled via wireless links, brings with it a plethora of vulnerabilities. Adversaries capable of imitating authorized device programmers could gain control over IMDs, leading to serious injury or even death of their users. Other attacks could target a patient’s private medical data. This thesis strives to give an overview over the current state of research and recent developments in the field of IMD-security and privacy. It will discuss known vulnerabilities and possible defensive measures and evaluate the current risks involved with using a modern IMD. Based on these discussions, design concerns for IMD manufacturers are then summarized. Bachelorarbeit 2012 5 25 Institut für Medieninformatik, Universität Ulm 1 BA, AA, StephanKleber, MichaelWeber Gerhard Habiger