Experience report: Memory accesses for avionic applications and operating systems on a multi-core platform

Löfwenmark, Andreas; Nadjm‐Tehrani, Simin

doi:10.1109/issre.2015.7381809

Cited by 3 publications

(1 citation statement)

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“…Multicore platforms are finding their way into the deployment of avionic systems due to their ability to leverage the computing capabilities, reduce the weight of on-board computing equipment and lower the energy consumption. However, due to safety-criticality requirements and the complexity resulting from the architectures of software and execution platforms, analyzing the schedulability of avionic systems is a challenging task [4]- [7].…”

Section: Introductionmentioning

confidence: 99%

Compositional Schedulability Analysis of Multicore Modular Avionic Architectures

Boudjadar¹

2018

JCP

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This paper presents a compositional schedulability analysis of multicore modular avionic systems (IMA). It provides a fine grained description of the software architecture and behavior to reduce the over-approximation, and a holistic analysis to check schedulability while considering computation requirements and shared memory interference. The system is structured in terms of subsystems, encapsulating ARINC653 partitions, each of which runs on a processing core. The schedulability analysis is performed for each subsystem individually while accounting for the memory interference that would result if the core under analysis runs effectively alongside with the rest of cores. Thereafter, we introduce an architecting technique to relocate functions between tasks located at the same partition in case of non schedulability, to derive potential schedulable system configurations delivering the same functionality. Schedulability is formally analyzed using Uppaal model checker. Our evaluation results show that our compositional analysis technique consumes up to 95% less than regular analysis, in terms of analysis time and memory space. 1202 perfect memory access i.e., the memory is immediately available whenever an access request occurs (hits) [6]- [9]. Such an estimation of the WCET at task level is most likely under-approximating. We believe that estimating the execution time at a lower level of the granularity (e.g. function level) results in less underapproximation of the execution time. Thus, the more granular the behavior representation is, the more optimistic the WCET will be. The under-approximation difference between task and function levels could be non comparable and would increase drastically with fine grained description levels.The interference resulting from shared memories and communication means (buses, networks) is a determinant factor in the schedulability of component-based real-time system. The interference time is in fact related to the number of concurrent components and the bandwidth of shared resources. Accordingly, accurate schedulability techniques require a holistic analysis where both computation and memory interference/ communication have to be considered together [10], [5].A surge of progress has been achieved in the area of schedulability analysis of multicore systems through an intensive use of model-based settings and formal methods. However, due to the systems size in avionics, given by the integration of huge number of concurrent applications, the use of formal methods can end up in state space explosion. Different techniques have been considered to bypass the state space explosion and provide upper bound guarantees on the schedulability, we cite abstraction-based [11], compositional analysis [12] and incremental analysis [13]. In this paper, we introduce a model-based framework for fine grained modeling and formal schedulability analysis of multicore avionic (IMA-driven) systems with shared memories. The system is structured in terms of subsystems, encapsulating ARINC653 partitions, each ...

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Section: Introductionmentioning

confidence: 99%