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This position paper provides first, a literature survey of selected domains with significant contributions to simulation interoperability research, such as defense and healthcare simulation, including insights from academia and research organizations. Next, four main interoperability methods are reviewed, i.e., messages-oriented methods, use of information exchange models and common object models, and reference modeling, including ontological means. This review leads to the observation that successful approaches do not only rely on technical solutions but are also using conceptual alignment of the underlying models as well. The Levels of Conceptual Interoperability Model is revisited to consider how it contributed—and still contributes today—to reach meaningful interoperability between model-based solutions. Its descriptive and prescriptive use is discussed, and it is applied to the four methods to show its practical applicability. [ABSTRACT FROM AUTHOR]

Entropy can signify different things. For instance, heat transfer in thermodynamics or a measure of information in data analysis. Many entropies have been introduced, and it can be difficult to ascertain their respective importance and merits. Here, we consider entropy in an abstract sense, as a functional on a probability space, and we review how being able to handle the trivial case of non-interacting systems, together with the subtle requirement of extensivity, allows for a systematic classification of the functional form. [ABSTRACT FROM AUTHOR]

Security is a major concern when building large-scale computer systems. Cloud services have made it easier to provision large-scale systems on demand over the Internet. While the cloud service providers provide the required building blocks such as compute units, database servers, and storage, customers are still responsible for securely combining these systems to satisfy their organization’s security policy. The secure development and operation of such large-scale systems present technical challenges. Composing a larger system using components with known security properties that satisfy a given security policy without re-analyzing the individual components is a difficult problem. In this study, we attempted to analyze the composability of components from a security perspective using first-order predicate logic. We posit that if we build a system using individual components that satisfy a security policy, the composed system will be sound with regard to that policy. Additionally, the methodology can be used to identify drifts or violations during future changes in the system by running checks during the system release cycles for continuous verification.

Decentralized finance (DeFi) has revolutionized the financial industry in recent years. Industries such as banking, insurance, and investment are experiencing a significant shift due to the growth of DeFi. The decentralized finance market is expanding exponentially, emphasizing the potential of digital currencies and decentralized platforms in providing an alternative to the traditional finance paradigm. It eliminates the need for costly intermediaries, reduces transaction fees, and increases accessibility to financial services for everyone, regardless of their geographic location or economic status. With the enormous increase in cryptocurrency investment, individuals and institutions have started to use DeFi. In this context, understanding the architecture and working mechanisms of different DeFi protocols becomes crucial in creating new and innovative products. This review paper explores various DeFi protocols, including derivatives, decentralized exchanges (DEX), lending and borrowing, asset management, and stablecoins. It analyses their internal structure and composability, providing insights into how these protocols can be combined to create new and innovative DeFi products and explore the potential of DeFi in providing an alternative to the traditional finance paradigm.

A proof-of-location ( $pol$ ) is a digital credential issued to a user after proving their location to an issuer. The user can use the $pol$ at a later time to prove to a verifier that they have been present at a claimed location. A secure Proof-of-Location (POL) system requires that $pol\text{s}$ be unforgeable and non-transferable to other users. POL systems can be used to provide fine-grained authentication and authorization and must ensure the privacy of the $pol$ owner against the issuer and the verifier while allowing efficient presentation of $pol\text{s}$ combined with other credentials when needed. Efficiency is in terms of communication overhead in user-verifier POL sessions, which has particular significance in high-volume $pol$ verification scenarios. We first propose a POL system that (i) is provably secure in a simulation-based framework, allowing a $pol$ to be securely used with other credentials, and (ii) provides anonymity against the issuer and the verifier. We then extend the system to allow $pol\text{s}$ to be stored on a public distributed ledger system and selectively be presented to the verifiers by the user. This is the first POL system that satisfies the above properties. We implement POL algorithms on a mobile phone and present our experimental results showing the practicality of the system. Our proposed scheme is highly scalable compared to existing systems, reducing the user-verifier POL communication overhead by up to a factor of 94.

Side-channel attacks are a fundamental threat to the security of cryptographic implementations. One of the most prominent countermeasures against side-channel attacks is masking, where each intermediate value of the computation is secret shared, thereby concealing the computation’s sensitive information. An important security model to study the security of masking schemes is the random probing model, in which the adversary obtains each intermediate value of the computation with some probability p. To construct secure masking schemes, an important building block is the refreshing gadget, which updates the randomness of the secret shared intermediate values. Recently, Dziembowski, Faust, and Zebrowski (ASIACRYPT’19) analyzed the security of a simple refreshing gadget by using a new technique called the leakage diagram. In this work, we follow the approach of Dziembowski et al. and significantly improve its methodology. Concretely, we refine the notion of a leakage diagram via so-called dependency graphs, and show how to use this technique for arbitrary complex circuits via composition results and approximation techniques. To illustrate the power of our new techniques, as a case study, we designed provably secure parallel gadgets for the random probing model, and adapted the ISW multiplication such that all gadgets can be parallelized. Finally, we evaluate concrete security levels, and show how our new methodology can further improve the concrete security level of masking schemes. This results in a compiler provable secure up to a noise level of O(1) for affine circuits and O(1/√n) in general.

Entropy can signify different things. For instance, heat transfer in thermodynamics or a measure of information in data analysis. Many entropies have been introduced, and it can be difficult to ascertain their respective importance and merits. Here, we consider entropy in an abstract sense, as a functional on a probability space, and we review how being able to handle the trivial case of non-interacting systems, together with the subtle requirement of extensivity, allows for a systematic classification of the functional form.

Decentralized finance (DeFi) has revolutionized the financial industry in recent years. Industries such as banking, insurance, and investment are experiencing a significant shift due to the growth of DeFi. The decentralized finance market is expanding exponentially, emphasizing the potential of digital currencies and decentralized platforms in providing an alternative to the traditional finance paradigm. It eliminates the need for costly intermediaries, reduces transaction fees, and increases accessibility to financial services for everyone, regardless of their geographic location or economic status. With the enormous increase in cryptocurrency investment, individuals and institutions have started to use DeFi. In this context, understanding the architecture and working mechanisms of different DeFi protocols becomes crucial in creating new and innovative products. This review paper explores various DeFi protocols, including derivatives, decentralized exchanges (DEX), lending and borrowing, asset management, and stablecoins. It analyses their internal structure and composability, providing insights into how these protocols can be combined to create new and innovative DeFi products and explore the potential of DeFi in providing an alternative to the traditional finance paradigm. [ABSTRACT FROM AUTHOR]

Albeit its many benefits, masking cryptographic hardware designs has proven to be a non-trivial and error-prone task, even for experienced engineers. Masked variants of atomic logic gates, like AND or XOR – commonly referred to as gadgets – aim to facilitate the process of masking large circuits by offering free composition while sustaining the overall design’s security in the d-probing adversary model. A wide variety of research has already been conducted to (i) find formal properties a gadget must fulfill to guarantee composability and (ii) construct gadgets that fulfill these properties, while minimizing overhead requirements. In all existing composition frameworks like NI/SNI/PINI and all corresponding gadget realizations, the security argument relies on the fact that each gadget requires individual fresh randomness. Naturally, this approach leads to very high randomness requirements of the resulting composed circuit. In this work, we present composable gadgets with reused fresh masks (COMAR), allowing the composition of any first-order secure hardware circuit utilizing only 6 fresh masks in total. By construction, our newly presented gadgets render individual fresh randomness unnecessary, while retaining free composition and first-order security in the robust probing model. More precisely, we give an instantiation of gadgets realizing arbitrary XOR and AND gates with an arbitrary number of inputs which can be trivially extended to all basic logic gates. With these, we break the linear dependency between the number of (non-linear) gates in a circuit and the randomness requirements, hence offering the designers the possibility to highly optimize a masked circuit’s randomness requirements while keeping error susceptibility to a minimum.

Mathematical modeling has become a major tool to guide the characterization and synthetic construction of cellular processes. However, models typically lose their capacity to explain or predict experimental outcomes as soon as any, even minor, modification of the studied system or its operating conditions is implemented. This limits our capacity to fully comprehend the functioning of natural biological processes and is a major roadblock for the de novo design of complex synthetic circuits. A common cause of this problem is that cell-to-cell variability creates couplings between single-cell circuits and population processes such as selection or growth. Altering the circuit may then have unforeseen consequences inside growing populations. Here we construct a yeast optogenetic differentiation system that exploits cell-to-cell variability to enable external control of the population composition. We show that a simple deterministic model can explain the dynamics of the core system. However, modifying the context of the circuit by expressing system components from plasmids leads to failure of model predictions. Subsequently, we deploy theory from stochastic chemical kinetics to construct models of the system's components that simultaneously track single-cell and population processes and demonstrate that this allows us to quantitatively predict emerging dynamics of the plasmid-based system without any adjustment of model parameters. We conclude that carefully characterizing the dynamics of cell-to-cell variability using appropriate modeling theory may allow one to unravel the complex interplay of stochastic single-cell and population processes and to predict the functionality of complex synthetic circuits in growing populations before the circuit is constructed. [ABSTRACT FROM AUTHOR]

Detailed maps of the molecular basis of the disease are powerful tools for interpreting data and building predictive models. Modularity and composability are considered necessary network features for large-scale collaborative efforts to build comprehensive molecular descriptions of disease mechanisms. An effective way to create and manage large systems is to compose multiple subsystems. Composable network components could effectively harness the contributions of many individuals and enable teams to seamlessly assemble many individual components into comprehensive maps. We examine manually built versions of the RAS–RAF–MEK–ERK cascade from the Atlas of Cancer Signalling Network, PANTHER and Reactome databases and review them in terms of their reusability and composability for assembling new disease models. We identify design principles for managing complex systems that could make it easier for investigators to share and reuse network components. We demonstrate the main challenges including incompatible levels of detail and ambiguous representation of complexes and highlight the need to address these challenges. [ABSTRACT FROM AUTHOR]

In a dynamic environment, a manufacturing system should be reconfigurable to make the products with lot size of one and a high product mix in mass customization. A manufacturing system is continuously evolved to make new products at different time scales and ensure uninterrupted productions when internal or external changes occur. System evolution relates to add, remove, upgrade components, and reconfigure the system at different levels and scopes. However, scientific methods and tools are lacking to support designers in reconfiguring a system subject to given changes. This becomes a big hurdle to adopt automated solutions in small- and medium-sized enterprises. To support system reconfiguration, we propose a generic framework and methods to assess the performance of heterogeneous robotic systems or components. The proposed methods can also help 1) designers to select components for an integrated solution based on the needs and 2) robot manufacturers to identify the weaknesses of their products. [ABSTRACT FROM AUTHOR]

Current simulation models are not only represented in the form of traditional data or formula for pure theory analysis but expanded to be simulation modeling assets that are featured with complicated structure, diverse behaviors, and abundant semantics. Semantic composability, therefore, receives a constantly growing attention in recent years. So far, one of the popular solutions to enhance semantic expressiveness is domain specific modeling based on general metamodeling (GMM) facilities. But for some particular domains, researchers identified the need of deeper semantic expressiveness therefore proposed domain specific metamodeling (DSMM). Hence, this paper aims to explore the underlying methodologies of DSMM for supporting deep semantic composability. Compared with several usual alternatives based on GMM, this paper applies the multi-level metamodeling architecture to create a set of metamodeling primitives using an example named SEvent. In fact, SEvent is a novel formalism that slightly extends Petri net to support continuous states transition and continuous event triggering. As a proof of concept, we concentrate on developing the textual syntax of SEvent and using it to represent torpedo's behaviors.

Refreshing algorithms are a critical ingredient for secure masking. They are instrumental in enabling sound composability properties for complex circuits, and their randomness requirements dominate the performance overheads in (very) high-order masking. In this paper, we improve a proposal of mask refreshing algorithms from EUROCRYPT 2017 that has excellent implementation properties in software and hardware, in two main directions. First, we provide a generic proof that this algorithm is secure at arbitrary orders—a problem that was left open so far. We introduce parametrized non-interference as a new technical ingredient for this purpose that may be of independent interest. Second, we use automated tools to further explore the design space of such algorithms and provide the best known parallel mask refreshing gadgets for concretely relevant security orders. Incidentally, we also prove the security of a recent proposal of mask refreshing with improved resistance against horizontal attacks from CHES 2017. [ABSTRACT FROM AUTHOR]

We improve the state-of-the-art masking schemes in two important directions. First, we propose a new masked multiplication algorithm that satisfies a recently introduced notion called Probe-Isolating Non-Interference (PINI). It captures a sufficient requirement for designing masked implementations in a trivial way, by combining PINI multiplications and linear operations performed share by share. Our improved algorithm has the best reported randomness complexity for large security orders (while the previous PINI multiplication was best for small orders). Second, we analyze the security of most existing multiplication algorithms in the literature against so-called horizontal attacks, which aim to reduce the noise of the actual leakages measured by an adversary, by combining the information of multiple target intermediate values. For this purpose, we leave the (abstract) probing model and consider a specialization of the (more realistic) noisy leakage / random probing models. Our (still partially heuristic but quantitative) analysis allows confirming the improved security of an algorithm by Battistello et al. from CHES 2016 in this setting. We then use it to propose new improved algorithms, leading to better tradeoffs between randomness complexity and noise rate, and suggesting the possibility to design efficient masked multiplication algorithms with constant noise rate in F2.

A lack of consistent data, reliable analysis techniques, and user-friendly tools is inhibiting decision makers' abilities to assess and evaluate the sustainability performance of manufacturing processes and systems. Recent integration of information technology with advanced manufacturing technologies has led to a new paradigm, termed smart manufacturing or Industry 4.0. To leverage this paradigm shift for the advancement of sustainable manufacturing, efforts have been made to characterize unit manufacturing processes (UMPs) for sustainability assessment and to develop frameworks, methodologies, and standards utilizing information modeling approaches. This paper proposes a grey box object-oriented software framework for sustainability assessment of complex manufacturing systems, utilizing the multiple inheritance principle for composition of UMP models. Information modeling guidelines based on the framework are provided for UMP model developers and UMP performance analysts to construct and analyze system models. To demonstrate the usefulness of the framework and guidelines, a prototype information model is developed for a hybrid manufacturing system composed of fused deposition modeling (an additive process) and CNC milling (a subtractive process). [ABSTRACT FROM AUTHOR]

We present a round-efficient black-box construction of a general multi-party computation (MPC) protocol that satisfies composability in the plain model. The security of our protocol is proven in the angel-based UC framework [Prabhakaran and Sahai, STOC'04] under the minimal assumption of the existence of semi-honest oblivious transfer protocols. The round complexity of our protocol is max(O~(log2n),O(ROT)) when the round complexity of the underlying oblivious transfer protocol is ROT. Since constant-round semi-honest oblivious transfer protocols can be constructed under standard assumptions (such as the existence of enhanced trapdoor permutations), our result gives a O~(log2n)-round protocol under these assumptions. Previously, only an O(max(nϵ,ROT))-round protocol was shown, where ϵ>0 is an arbitrary constant. We obtain our MPC protocol by constructing a O~(log2n)-round CCA-secure commitment scheme in a black-box way under the assumption of the existence of one-way functions. [ABSTRACT FROM AUTHOR]

Many-core platforms are rapidly expanding in various embedded areas as they provide the scalable computational power required to meet the ever-growing performance demands of embedded applications and systems. However, the huge design space of possible task mappings, the unpredictable workload dynamism, and the numerous non-functional requirements of applications in terms of timing, reliability, safety, and so forth. impose significant challenges when designing many-core systems. Hybrid Application Mapping (HAM) is an emerging class of design methodologies for many-core systems which address these challenges via an incremental (per-application) mapping scheme: The mapping process is divided into (i) a design-time Design Space Exploration (DSE) step per application to obtain a set of high-quality mapping options and (ii) a run-time system management step in which applications are launched dynamically (on demand) using the precomputed mappings. This paper provides an overview of HAM and the design methodologies developed in line with it. We introduce the basics of HAM and elaborate on the way it addresses the major challenges of application mapping in many-core systems. We provide an overview of the main challenges encountered when employing HAM and survey a collection of state-of-the-art techniques and methodologies proposed to address these challenges. We finally present an overview of open topics and challenges in HAM, provide a summary of emerging trends for addressing them particularly using machine learning, and outline possible future directions. While there exists a large body of HAM methodologies, the techniques studied in this paper are developed, to a large extent, within the scope of invasive computing. Invasive computing introduces resource awareness into applications and employs explicit resource reservation to enable incremental application mapping and dynamic system management.

Composability and robustness against physical defaults (e.g., glitches) are two highly desirable properties for secure implementations of masking schemes. While tools exist to guarantee them separately, no current formalism enables their joint investigation. In this paper, we solve this issue by introducing a new model, the robust probing model, that is naturally suited to capture the combination of these properties. We first motivate this formalism by analyzing the excellent robustness and low randomness requirements of first-order threshold implementations, and highlighting the difficulty to extend them to higher orders. Next, and most importantly, we use our theory to design and prove the first higher-order secure, robust and composable multiplication gadgets. While admittedly inspired by existing approaches to masking (e.g., Ishai-Sahai-Wagner-like, threshold, domain-oriented), these gadgets exhibit subtle implementation differences with these state-of-the-art solutions (none of which being provably composable and robust). Hence, our results illustrate how sound theoretical models can guide practically-relevant implementations.

In this paper a passive integrator dedicated to input/output Hamiltonian systems approximation is presented. In a first step, a discrete Hamiltonian framework endowed with a Lie derivative-like formula is introduced. It is shown that the discrete dynamics encodes energy conservation and passivity. Additionally, the characterization of the discrete dynamics in terms of Dirac structure is shown to be invariant by interconnection. The class is thus composable: networked systems belong to the class. In a second step, the discrete dynamics is considered as a one-step integration method. The method is shown to be convergent and provides a discrete-time approximation of an input/output Hamiltonian system. Accordingly, the discrete dynamics inherits intrinsic energetic characteristics (storage function and dissipation rate) from the original system. The method is thus tagged as passive integrator. As an illustration, the closed-loop behavior of interconnected subsystems and the stabilization of a rigid body spinning around its center of mass are presented. [ABSTRACT FROM AUTHOR]

The last two decades witnessed the success of many efficient designs of concurrent data structures. A large set of them has a common base principle: each operation is split into a read-only traversal phase, which scans the data structure without locking or monitoring, and a read-write commit phase, which atomically validates the output of the traversal phase and applies the needed modifications to the data structure. In this paper we introduce Optimistic Transactional Boosting (OTB), an optimistic methodology for extending those designs in order to support the composition of multiple operations into one atomic execution by building a single traversal phase and a single commit phase for the whole atomic execution. As a result, OTB-based data structures are optimistic and composable . The former because they defer any locking and/or monitoring to the commit phase of the entire atomic execution; the latter because they allow the execution of multiple operations atomically. Additionally, in this paper we provide a theoretical model for analyzing OTB-based data structures and proving their correctness. In particular, we extended a recent approach that models concurrent data structures by including the two notions of optimism and composition of operations. [ABSTRACT FROM AUTHOR]

We show that it is possible for the so-called weak locking capacity of a quantum channel (Guha et al. in Phys Rev X 4:011016, 2014) to be much larger than its private capacity. Both reflect different ways of capturing the notion of reliable communication via a quantum system while leaking almost no information to an eavesdropper; the difference is that the latter imposes an intrinsically quantum security criterion whereas the former requires only a weaker, classical condition. The channels for which this separation is most straightforward to establish are the complementary channels of classical-quantum (cq-)channels and, hence, a subclass of Hadamard channels. We also prove that certain symmetric channels (related to photon number splitting) have positive weak locking capacity in the presence of a vanishingly small pre-shared secret, whereas their private capacity is zero. These findings are powerful illustrations of the difference between two apparently natural notions of privacy in quantum systems, relevant also to quantum key distribution: the older, naïve one based on accessible information, contrasting with the new, composable one embracing the quantum nature of the eavesdropper's information. Assuming an additivity conjecture for constrained minimum output Rényi entropies, the techniques of the first part demonstrate a single-letter formula for the weak locking capacity of complements to cq-channels, coinciding with a general upper bound of Guha et al. for these channels. Furthermore, still assuming this additivity conjecture, this upper bound is given an operational interpretation for general channels as the maximum weak locking capacity of the channel activated by a suitable noiseless channel. [ABSTRACT FROM AUTHOR]

Seamless composability of disparate simulations within a systems of systems context is challenging. Large complex simulations must respond to changing technology, environments, and objectives. The problem exacerbates when dynamic extensibility and adaptability are significant concerns in an application domain. Simulations that are dynamically extensible, while being composable require principled designs that facilitate engineering interoperability and composability in the first place. The role of ontologies and their axiomatization is discussed as a potential strategy to improve dynamic composability.

The Levels of Conceptual Interoperability Model (LCIM) was developed to cope with the different layers of interoperation of modeling and simulation applications. It introduced technical, syntactic, semantic, pragmatic, dynamic, and conceptual layers of interoperation and showed how they are related to the ideas of integratability, interoperability, and composability. The model was successfully applied in various domains of systems, cybernetics, and informatics.

Efficiency of natural stone production processes in quarries directly affects the economic output and environmental performances, such as production lead times and energy consumptions. Knowledge on stone production processes is crucial in making responsible decisions in this business. Having a structured representation of information characterizing the stone production processes will support stakeholders in better assessing production resources in terms of sustainability and productivity. Value stream mapping can provide an overview and guidance for sustainability performance evaluation, but its application is limited. The challenges arise when trying to specifically map and relate sustainability data between processes e.g., variability in lead time and CO 2 emissions. Manufacturing process characterization standards currently being developed by ASTM International manifest the potential to not only fill this gap but also to provide opportunities to characterize and compose manufacturing processes with relevant environmental information and description. This paper shows the application and lessons learned from deploying one such effort towards standardization. [ABSTRACT FROM AUTHOR]

Multi-Processor Systems-on-a-Chip (MPSoCs) provide sufficient computing power for many applications in scientific as well as embedded applications. Unfortunately, when real-time requirements need to be guaranteed, applications suffer from the interference with other applications, uncertainty of dynamic workload and state of the hardware. Composable application/architecture design and timing analysis is therefore a must for guaranteeing real-time applications to satisfy their timing requirements independent from dynamic workload. Here, Invasive Computing is used as the key enabler for compositional timing analysis on MPSoCs, as it provides the required isolation of resources allocated to each application. On the basis of this paradigm, this work proposes a hybrid application mapping methodology that combines design-time analysis of application mappings with run-time management. Design space exploration delivers several resource reservation configurations with verified real-time guarantees for individual applications. These timing properties can then be guaranteed at run-time, as long as dynamic resource allocations comply with the offline analyzed resource configurations. This article describes our methodology and presents programming, optimization, analysis, and hardware techniques for enforcing timing predictability. A case study illustrates the timing-predictable management of real-time computer vision applications in dynamic robot system scenarios. [ABSTRACT FROM AUTHOR]

Modeling and simulation is pervasive throughout many different disciplines. As computing technology has provided more capability, the systems being modeled and simulated have grown larger and more complex. Often times, these large systems are managed as interacting subsystems. When it is necessary for the simulation to allow disparate subsystems to maintain their independence, then a hybrid model of the subsystems should be used. Furthermore, to ease the burden of verification and validation of simulation results, a proven system theoretical modeling specification should be used. However, many communities have already adopted nonsystem theoretical software solutions and established a group of domain experts familiar with these tools. This paper provides two things: a formal approach to building a hybrid model, and a discussion of how to incorporate a nonsystem theoretical software implementation into a proven framework. The first is done through the implementation of a Knowledge Interchange Broker (KIB) as an Interaction Model (IM). The second is accomplished by exemplifying the use of the IM in an agent-environment hybrid model. In the hybrid model, the agent is implemented in the Discrete-event System (DEVS) specification and the environment is implemented in the Geographical Resources Analysis Support System (GRASS) using a Composable Cellular Automaton (CCA) specification. This concept has been successfully applied to both example models and an interdisciplinary research project where the interactions between human activities and landscape processes are studied. [ABSTRACT FROM AUTHOR]

Quantum computing has seen tremendous progress in the past few years. However, due to limitations in the scalability of quantum technologies, it seems that we are far from constructing universal quantum computers for everyday users. A more feasible solution is the delegation of computation to powerful quantum servers on the network. This solution was proposed in previous studies of blind quantum computation, with guarantees for both the secrecy of the input and of the computation being performed. In this work, we further develop this idea of computing over encrypted data, to propose a multiparty delegated quantum computing protocol in the measurement-based quantum computing framework. We prove the security of the protocol against a dishonest server and against dishonest clients, under the assumption of common classical cryptographic constructions.

Triple-modular-redundant applications are widely used for fault-tolerant safety–critical computation. They have strict timing requirements for correct operation. We present an architecture which provides composability and mixed-criticality to support integration and to ease certification of such safety–critical applications. In this architecture, an additional layer is required for the sharing/partitioning of resources. This potentially jeopardizes the synchronization necessary for the triple-modular-redundant applications. We investigate the effects of different (unsynchronized) scheduling methods for the resource-sharing layer in this architecture and conclude that an out-of-the-box solution, which guarantees the technical separation between applications with fast reaction time requirements is only feasible when executing at most one instance of a triple-modular-redundant application per CPU-core for single and multi-core CPUs. Only when accepting changes in the applications or the applications’ synchronization mechanisms, are more flexible solutions with good performance and resource utilization available. [ABSTRACT FROM AUTHOR]

Modeling & Simulation (M&S) is making successful contributions to different areas in industry and academia. However, there are certain key issues that are preventing the field from addressing larger domains and from achieving wide-scale impact. Formulating these as grand challenges arguably focuses attention on these key issues and may bring a critical mass of effort to bear that could result in a major leap forward. This article is one of several concurrent activities aimed at reinvigorating the debate on grand challenges in M&S. These grand challenges include Big Simulation, human behavior, composability, cloud-based M&S, reproducibility in M&S research and the democratization of M&S. Two themes emerge: the need for large-scale cloud-based cyberinfrastructures for M&S and the democratized access to M&S and its outputs. [ABSTRACT FROM AUTHOR]

We present Abstract (ABortable STate mAChine replicaTion), a new abstraction for designing and reconfiguring generalized replicated state machines that are, unlike traditional state machines, allowed to abort executing a client's request if "something goes wrong." Abstract can be used to considerably simplify the incremental development of efficient Byzantine faulttolerant state machine replication (BFT) protocols that are notorious for being difficult to develop. In short, we treat a BFT protocol as a composition of Abstract instances. Each instance is developed and analyzed independently and optimized for specific system conditions. We illustrate the power of Abstract through several interesting examples. We first show how Abstract can yield benefits of a state-of-the-art BFT protocol in a less painful and errorprone manner. Namely, we develop AZyzzyva, a new protocol that mimics the celebrated best-case behavior of Zyzzyva using less than 35% of the Zyzzyva code. To cover worst-case situations, our abstraction enables one to use in AZyzzyva any existing BFT protocol. We then present Aliph, a new BFT protocol that outperforms previous BFT protocols in terms of both latency (by up to 360%) and throughput (by up to 30%). Finally, we present R-Aliph, an implementation of Aliph that is robust, that is, whose performance degrades gracefully in the presence of Byzantine replicas and Byzantine clients. [ABSTRACT FROM AUTHOR]