Finding a barrier-free accessible path through the built environment is necessary for wheelchair users. Researchers have identified the effect of surface vibration on the health of wheelchair users and proposed variou...
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Bitcoin was released in 2008 as an electronic peer-to-peer payment system. The aim was to enable financial transactions in an anonymous manner between participating parties. However, Bitcoin is considered a pseudonymo...
Bitcoin was released in 2008 as an electronic peer-to-peer payment system. The aim was to enable financial transactions in an anonymous manner between participating parties. However, Bitcoin is considered a pseudonymous network rather than anonymous, as the identity of the address owner is unknown, but every transaction is permanently stored on the Bitcoin blockchain and can be tracked by anyone. The structure of the blockchain, its transactions, and the Bitcoin network make it possible to deanonymize pseudonyms through various methods such as flow analysis, heuristics, and network traffic observations. Once a connection is established between pseudonyms used in the Bitcoin network and the real world, all previous transactions can be attributed to that identity. In 2021, Taproot was introduced to further increase privacy within the Bitcoin Network by introducing a new address format which will allow transactions to be more indistinguishable from one another. In this paper, we analyze current methods for deanonymizing Bitcoin transactions to understand which parts of the Bitcoin protocol they exploit. In addition, we look at the changes introduced by Taproot and determine the extent to which these changes affect the methods and what assumptions must be made for these methods to remain applicable.
Concurrency control algorithms are key determinants of the performance of in-memory databases. Existing algorithms are designed to work well for certain workloads. For example, optimistic concurrency control (OCC) is ...
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Task migration is a potent instrument to exploit multi-core processors. Like full preemption, full migration is particularly advantageous as it allows the scheduler to relocate tasks at arbitrary times between cores. ...
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ISBN:
(数字)9781728164632
ISBN:
(纸本)9781728164649
Task migration is a potent instrument to exploit multi-core processors. Like full preemption, full migration is particularly advantageous as it allows the scheduler to relocate tasks at arbitrary times between cores. However, in hard real-time systems, migration is accompanied by a tremendous drawback: poor predictability and thus inevitable overapproximations in the worst-case execution-time analysis. This is due to the non-constant size of the tasks' resident set and the costs associated with its transfer between cores. As a result, migration is banned in many real-time systems, regressing the developer to a static allocation of tasks to cores with disadvantageous effects on the overall utilization and schedulability. In previous work, we successfully alleviated the shortcomings of full migration in real-time systems by reducing the associated costs and increasing its predictability. By employing static analysis, we were able to identify beneficial migration points and thus generate static schedules migrating tasks at these identified points. In ongoing work, we extend this approach to dynamic scheduling by providing information about advantageous migration points to an operating system which then makes migration decisions at runtime.
Reliable and fine-grained cost-models are fundamental for real-time systems to statically predict worst-case execution time (WCET) estimates of program code in order to guarantee timeliness. Analogous considerations h...
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Reliable and fine-grained cost-models are fundamental for real-time systems to statically predict worst-case execution time (WCET) estimates of program code in order to guarantee timeliness. Analogous considerations hold for energy-constrained systems where worst-case energy consumption (WCEC) values are mandatory to ensure meeting predefined energy budgets. These cost models are generally unavailable for commercial off-the-shelf (COTS) hardware platforms, although static worst-case analysis tools require those models in order to predict the WCET as well as the WCEC of program code. To solve this problem, we present NEO, an end-to-end toolchain to automate cost-model generation for both WCET and WCEC analyses. NEO exploits automatically generated benchmarks, which are input for 1) an instruction-level emulation and 2) automatically conducted execution-time and energy-consumption measurements on the target platform. The gathered values (i.e., occurrences per instruction, execution-time and energyconsumption per benchmark) are combined as mathematical optimization problems. The solutions to the formulated problems, which are designed to reveal the worst-case behavior, yield the respective cost models. To statically determine upper bounds of benchmarks, we integrated the cost models into the stateof-the-art WCET analyzer PLATIN. Our evaluations on COTS hardware reveal that our open-source, end-to-end toolchain NEO yields accurate worst-case bounds.
作者：
Honig, Timo
Department of Computer Science Distributed Systems and Operating Systems Martensstr. 1 ErlangenD-91058 Germany
From an ecological and economic perspective, saving energy is an important factor for the design of today's computing systems. However, building energy-efficient systems is a challenging task for system designers....
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ISBN:
(纸本)9783885796404
From an ecological and economic perspective, saving energy is an important factor for the design of today's computing systems. However, building energy-efficient systems is a challenging task for system designers. It requires exact knowledge about the system's components (i.e., software and hardware components) and it is not immediately obvious how the energy demand of a system can be improved. This paper presents energy-aware programming techniques that help developers at optimizing the energy demand of software. Such techniques address sensibility aspects (i.e., energy awareness) and provide optimization suggestions to developers. The paper further discusses responsibility aspects that emerge from the advent of energy-aware programming techniques.
Arithmetic error coding schemes (AN codes) are a well known and effective technique for soft error mitigation. Although coding theory being a rich area of mathematics, their implementation seems to be fairly easy. How...
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Arithmetic error coding schemes (AN codes) are a well known and effective technique for soft error mitigation. Although coding theory being a rich area of mathematics, their implementation seems to be fairly easy. However, compliance with the theory can be lost easily while moving towards an actual implementation - finally jeopardizing the aspired fault-tolerance characteristics. In this paper, we present our experiences and lessons learned from implementing AN codes in the Cored dependable voter. We focus on the challenges and pitfalls in the transition from maths to machine code for a binary computer from a systems perspective. Our results show, that practical misconceptions (such as the use of prime numbers) and architecture-dependent implementation glitches occur on every stage of this transition. We identify typical pitfalls and describe practical measures to find and resolve them. Our measures eliminate all remaining SDCs in the Cored voter, which is validated by an extensive fault-injection campaign that covers 100 percent of the fault space for 1-bit and 2-bit errors.
In the biotechnology field, the deployment of the Multiple Sequence Alignment (MSA) problem, which is a high performance computing demanding process, is one of the new challenges to address on the new parallel systems...
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Ecosystem functioning, climate change, and multiple interactions among biogeochemical cycles, climate system, site conditions and land use options are leading-edge topics in recent environmental modelling. Terrestrial...
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Ecosystem functioning, climate change, and multiple interactions among biogeochemical cycles, climate system, site conditions and land use options are leading-edge topics in recent environmental modelling. Terrestrial ecosystem models are widely used to support carbon sequestration and ecosystem studies under various ecological circumstances. Our team uses the Biome-BGC model (Numerical Terradynamic Simulation Group, University of Montana), and develops an improved model version of it, called Biome-BGC MuSo. Both the original and the improved model estimate the ecosystem scale storage and fluxes of energy, carbon, nitrogen and water, controlled by various physical and biological processes on a daily time-scale. Web services were also developed and integrated with parallel processing desktop grid technology. Taverna workflow management system was used to build up and carry out elaborated workflows like seamless data flow to model simulation, Monte Carlo experiment, model sensitivity analysis, model-data fusion, estimation of ecosystem service indicators or extensive spatial modelling. Straightforward management of complex data analysis tasks, organized into appropriately documented, shared and reusable scientific workflows enables researchers to carry out detailed and scientifically challenging 'in silico' experiments and applications that could open new directions in ecosystem research and in a broader sense it supports progress in environmental modelling. The workflow approach built upon these web services allows even the most complicated computations to be initiated without the need of programming skills and deep understanding of model structure and initialization. The developments enable a wider array of scientists to perform ecosystem scale simulations, and to perform analyses not previously possible due to high complexity and computational demand.
Five teams participated in the Multi-Agent Programming Contest in 2013: All of them gained experience in 2012 already. In order to better understand which paradigms they used, which techniques they considered importan...
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