arXiv subjects

Luiz Maia

Publications and source records attributed to Luiz Maia.

3 recordsLinked to original sources

arXiv2025

Decreasing Utilization of Systems with Multi-Rate Cause-Effect Chains While Reducing End-to-End Latencies

The Logical Execution Time (LET) model has deterministic properties which dramatically reduce the complexity of analyzing temporal requirements of multi-rate cause-effect chains. The configuration (length and position) of task's communication intervals directly define which task instances propagate data through the chain and affect end-to-end latencies. Since not all task instances propagate data through the chain, the execution of these instances wastes processing resources. By manipulating the configuration of communication intervals, it is possible to control which task instances are relevant for data propagation and end-to-end latencies. However, since tasks can belong to more than one cause-effect chain, the problem of configuring communication intervals becomes non-trivial given the large number of possible configurations. In this paper, we present a method to decrease the waste of processing resources while reducing end-to-end latencies. We use a search algorithm to analyze different communication interval configurations and find the combination that best decrease system utilization while reducing end-to-end latencies. By controlling data propagation by means of precedence constraints, our method modifies communication intervals and controls which task instances affect end-to-end latencies. Despite the sporadic release time of some task instances during the analysis, our method transforms those instances into periodic tasks. We evaluate our work using synthetic task sets and the automotive benchmark proposed by BOSCH for the WATERS industrial challenge.

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arXiv2024

Reducing End-to-End Latencies of Multi-Rate Cause-Effect Chains for the LET Model

The Logical Execution Time (LET) model has been gaining industrial attention because of its timing and data-flow deterministic characteristics, which simplify the computation of end-to-end latencies of multi-rate cause-effect chains at the cost of pessimistic latencies. In this paper, we propose a novel method to reduce the pessimism in the latencies introduced by LET, while maintaining its determinism. We propose a schedule-aware LET model that shortens the lengths and repositions LET's communication intervals resulting in less pessimistic end-to-end latencies. By adding dependencies between specific task instances, the method can further reduce the pessimism in the latency calculations of the LET model. If needed, e.g., for legacy reasons, our method can be applied to a subset of tasks only. We evaluate our work based on real world automotive benchmarks and randomly generated synthetic task sets. We compare our results with previous work and the LET model. The experiments show significant reductions of worst-case data age and worst-case reaction latency values.

eess.SY↗

arXiv2024

Safety-Critical Edge Robotics Architecture with Bounded End-to-End Latency

Edge computing processes data near its source, reducing latency and enhancing security compared to traditional cloud computing while providing its benefits. This paper explores edge computing for migrating an existing safety-critical robotics use case from an onboard dedicated hardware solution. We propose an edge robotics architecture based on Linux, Docker containers, Kubernetes, and a local wireless area network based on the TTWiFi protocol. Inspired by previous work on real-time cloud, we complement the architecture with a resource management and orchestration layer to help Linux manage, and Kubernetes orchestrate the system-wide shared resources (e.g., caches, memory bandwidth, and network). Our architecture aims to ensure the fault-tolerant and predictable execution of robotic applications (e.g., path planning) on the edge while upper-bounding the end-to-end latency and ensuring the best possible quality of service without jeopardizing safety and security.

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