60 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Resilient and Scalable Forwarding for Software-Defined Networks with P4-Programmable Switches

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    Traditional networking devices support only fixed features and limited configurability. Network softwarization leverages programmable software and hardware platforms to remove those limitations. In this context the concept of programmable data planes allows directly to program the packet processing pipeline of networking devices and create custom control plane algorithms. This flexibility enables the design of novel networking mechanisms where the status quo struggles to meet high demands of next-generation networks like 5G, Internet of Things, cloud computing, and industry 4.0. P4 is the most popular technology to implement programmable data planes. However, programmable data planes, and in particular, the P4 technology, emerged only recently. Thus, P4 support for some well-established networking concepts is still lacking and several issues remain unsolved due to the different characteristics of programmable data planes in comparison to traditional networking. The research of this thesis focuses on two open issues of programmable data planes. First, it develops resilient and efficient forwarding mechanisms for the P4 data plane as there are no satisfying state of the art best practices yet. Second, it enables BIER in high-performance P4 data planes. BIER is a novel, scalable, and efficient transport mechanism for IP multicast traffic which has only very limited support of high-performance forwarding platforms yet. The main results of this thesis are published as 8 peer-reviewed and one post-publication peer-reviewed publication. The results cover the development of suitable resilience mechanisms for P4 data planes, the development and implementation of resilient BIER forwarding in P4, and the extensive evaluations of all developed and implemented mechanisms. Furthermore, the results contain a comprehensive P4 literature study. Two more peer-reviewed papers contain additional content that is not directly related to the main results. They implement congestion avoidance mechanisms in P4 and develop a scheduling concept to find cost-optimized load schedules based on day-ahead forecasts

    The Computational Power of Distributed Shared-Memory Models with Bounded-Size Registers

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    The celebrated Asynchronous Computability Theorem of Herlihy and Shavit (STOC 1993 and STOC 1994) provided a topological characterization of the tasks that are solvable in a distributed system where processes are communicating by writing and reading shared registers, and where any number of processes can fail by crashing. However, this characterization assumes the use of full-information protocols, that is, protocols in which each time any of the processes writes in the shared memory, it communicates everything it learned since the beginning of the execution. Thus, the characterization implicitly assumes that each register in the shared memory is of unbounded size. Whether unbounded size registers are unavoidable for the model of computation to be universal is the central question studied in this paper. Specifically, is any task that is solvable using unbounded registers solvable using registers of bounded size? More generally, when at most tt processes can crash, is the model with bounded size registers universal? These are the questions answered in this paper

    Sex & Drugs & Rock’n’Roll A moral Odyssey retold by Homer, Joyce and Duchamp

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    In 2023, one century after Marcel Duchamp completed his work on the Large Glass, a book comes to suggest that it is not self-referential but has specific protagonists, locations and details that convey a timeless moral lesson about archetypal issues that human nature is perpetually tormented with – Sex (lust) & Drugs (intoxication) & Rock’n’Roll (violence). By choice, Duchamp never directly referred to Homer regarding the Glass, and this work has been analysed by many scholars in different ways. When Dr Megakles Rogakos came across the work in 2000, the detail of the Oculist Witnesses on it prompted him to sense their possible connection with the Trial of the Bow in Homer’s Odyssey, and he spoke about it in a related talk at London’s Tate Gallery on 10 August of the same year. He made this theory the subject of his PhD thesis (2012-2016) at the University of Essex entitled “A Joycean Exegesis of The Large Glass: Homeric Traces in the Postmodernism of Marcel Duchamp”. The Homeric exegesis of Duchamp’s Glass through Joyce’s Ulysses aims to confirm the atavistic theory that the ancient is present in the contemporary. The Glass, like the Homeric Odyssey, as revisited in Ulysses, may be thought to be some kind of moralising treatise on the temptations of man to fall prey to the three deadliest sins throughout human history – lust of flesh; indulgence in drugs; craving for power, as discussed separately in chapters of the book (see III.9; III.8; III.12) and gave its title – “Sex & Drugs & Rock’n’Roll”, after Ian Dury’s censored song of 1977. If its Joycean exegesis is proven, then the Glass may enigmatically emerge as a Homeric paradigm of man’s initiation to inner freedom, which Duchamp called the “beauty of indifference”. Dr Eleftherios Anevlavis, translator of Joyce’s Ulysses and Wake, writes: “Dr Rogakos’ exegesis is an impressive intellectual creation, enriched with the practices of decipherment and the art of writing, but at the same time created by the experiences and exhaustive study of culture from Homer to Yoko Ono and of the cosmos from the cave paintings of Lascaux to the constellation of the Pleiades.” Remarkably, with his theory of the appropriation of Homer’s Odyssey in Duchamp’s Glass, Dr Rogakos offers a refreshingly tongue-in-cheek explanation of postmodernism’s relationship to antiquity

    Tools and Algorithms for the Construction and Analysis of Systems

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    This open access book constitutes the proceedings of the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2022, which was held during April 2-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 46 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 159 submissions. The proceedings also contain 16 tool papers of the affiliated competition SV-Comp and 1 paper consisting of the competition report. TACAS is a forum for researchers, developers, and users interested in rigorously based tools and algorithms for the construction and analysis of systems. The conference aims to bridge the gaps between different communities with this common interest and to support them in their quest to improve the utility, reliability, exibility, and efficiency of tools and algorithms for building computer-controlled systems

    Developing an Effective Detection Framework for Targeted Ransomware Attacks in Brownfield Industrial Internet of Things

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    The Industrial Internet of Things (IIoT) is being interconnected with many critical industrial activities, creating major cyber security concerns. The key concern is with edge systems of Brownfield IIoT, where new devices and technologies are deployed to interoperate with legacy industrial control systems and leverage the benefits of IoT. These edge devices, such as edge gateways, have opened the way to advanced attacks such as targeted ransomware. Various pre-existing security solutions can detect and mitigate such attacks but are often ineffective due to the heterogeneous nature of the IIoT devices and protocols and their interoperability demands. Consequently, developing new detection solutions is essential. The key challenges in developing detection solutions for targeted ransomware attacks in IIoT systems include 1) understanding attacks and their behaviour, 2) designing accurate IIoT system models to test attacks, 3) obtaining realistic data representing IIoT systems' activities and connectivities, and 4) identifying attacks. This thesis provides important contributions to the research focusing on investigating targeted ransomware attacks against IIoT edge systems and developing a new detection framework. The first contribution is developing the world's first example of ransomware, specifically targeting IIoT edge gateways. The experiments' results demonstrate that such an attack is now possible on edge gateways. Also, the kernel-related activity parameters appear to be significant indicators of the crypto-ransomware attacks' behaviour, much more so than for similar attacks in workstations. The second contribution is developing a new holistic end-to-end IIoT security testbed (i.e., Brown-IIoTbed) that can be easily reproduced and reconfigured to support new processes and security scenarios. The results prove that Brown-IIoTbed operates efficiently in terms of its functions and security testing. The third contribution is generating a first-of-its-kind dataset tailored for IIoT systems covering targeted ransomware attacks and their activities, called X-IIoTID. The dataset includes connectivity- and device-agnostic features collected from various data sources. The final contribution is developing a new asynchronous peer-to-peer federated deep learning framework tailored for IIoT edge gateways for detecting targeted ransomware attacks. The framework's effectiveness has been evaluated against pre-existing datasets and the newly developed X-IIoTID dataset

    Applied Methuerstic computing

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    For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

    Statically Safe Distributed Programming

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    The Internet and the services it provides have become an omnipresent part of our lives. Asynchronous distributed systems form the basis of these services. Resiliency in the face of partial failures is an essential requirement for many distributed systems, meaning the systems must continue to function as specified even if several components fail. Ensuring correct behavior, particularly when it comes to failures and asynchrony, makes programming such systems very challenging. Multiparty session types (MPSTs) is a typing discipline for concurrent processes that statically ensures desired properties, such as the absence of message reception errors and deadlocks. These properties can help developers implement correct asynchronous message-passing applications. However, existing MPSTs do not support the specification and verification of partial failure-handling or practical fault-tolerant protocols that handle and recover from partial failures. This fundamentally limits the applicability of MPSTs to asynchronous real-world distributed systems. In this thesis we present our article “A Typing Discipline for Statically Verified Crash Failure Handling in Distributed Systems” [VCE+ 18], which is the first MPST formulation for crash failure handling in asynchronous distributed systems. This work features a lightweight coordinator modeled after widely used systems such as Apache ZooKeeper and Chubby. For this formulation we developed a typing discipline based on MPSTs that supports the specification and static verification of multiparty protocols with failure handling. The model preserves the distributed nature of MPSTs and interacts only with the lightweight coordinator for the purpose of critical decision-making around failure handling. The type system provides subject reduction despite the possibility of failures occurring at runtime. We implemented our formulation as a prototype in Scala, using Apache ZooKeeper for coordination, and used it to implement and verify a distributed logistic regression (LR) model. In the accompanying performance evaluation, the session type distributed LR model has a performance comparable to failure agnostics distributed LR models in the absence of failures. We also present our article, “A Multiparty Session Typing Discipline for Fault-tolerant Event-driven Distributed Programming” [VHEZ21], which combines ideas from the previous model with observations from fault-tolerant middleware systems. This work is the first formulation of MPSTs for practical fault-tolerant distributed programming of asynchronous distributed systems. In this work, we give structure to communication patterns involving asynchronous communication and concurrent failures and integrate the features required to express practical fault-tolerant protocols involving dynamic replacement of failed parties and the retrying of failed protocol segments in the presence of imperfect failure detection (perfect failure detection is impossible in asynchronous distributed systems). Key to our approach is the development of the first model of event-driven concurrency for multiparty sessions to unify the session-typed handling of failures and regular I/O events. Moreover, the characteristics of our model allow us to prove a global progress property for well-typed processes engaged in multiple concurrent sessions. Global progress traditionally does not hold in MPST systems. To demonstrate its practicality, we implement our approach as a toolchain for Scala and use it to specify and implement a session-typed version of the cluster manager (CM) of the widely employed Apache Spark data analytics engine. Our session-typed CM integrates with other vanilla Spark components to give a functioning Spark runtime, i.e., it can execute existing unmodified third-party Spark applications. Measured on an industry-standard benchmark Apache Spark has an average performance overhead below 10% when using our session-typed CM instead of Spark’s default CM, in the absence of failures. The developed MPSTs typing disciplines and prototypes enable the specification and verification of practical distributed applications that handle partial failures. Thus, we enable the verification of desired properties and, in turn, help develop correct distributed applications

    Applied Metaheuristic Computing

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    For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC
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