Measurement-Based Probabilistic Timing Analysis (MBPTA) has been recently proposed as a viable method to compute probabilistic worst-case execution time (pWCET) bounds for programs with hard real-time constraints. As a key trait, MBPTA needs a comparatively small number of observation runs, made on execution platforms to which MBPTA can be applied, to project the tail of the probability of occurrence of worst-case execution time durations of individual programs. In order for the use of MBPTA to fit the bill of industrial-quality development, it is imperative to understand what factors might threaten the trustworthiness of the pWCET computation. This paper addresses that important question by: (i) identifying the combined characteristics of applications and hardware resources that might lead to optimistic pWCET bounds, (ii) describing why this may occur, and (iii) providing the user with means to detect those cases so that trustworthiness is restored. In particular, we present a method for detecting risk scenarios for time-randomised caches, based on principles that apply to any other time-randomised resource which may challenge the application of MBPTA.
Heart of Gold: Making the Improbable Happen to Increase Confidence in MBPTA2014 26th Euromicro Conference on Real-Time Systems
VARDANEGA, TULLIO;
2014
Abstract
Measurement-Based Probabilistic Timing Analysis (MBPTA) has been recently proposed as a viable method to compute probabilistic worst-case execution time (pWCET) bounds for programs with hard real-time constraints. As a key trait, MBPTA needs a comparatively small number of observation runs, made on execution platforms to which MBPTA can be applied, to project the tail of the probability of occurrence of worst-case execution time durations of individual programs. In order for the use of MBPTA to fit the bill of industrial-quality development, it is imperative to understand what factors might threaten the trustworthiness of the pWCET computation. This paper addresses that important question by: (i) identifying the combined characteristics of applications and hardware resources that might lead to optimistic pWCET bounds, (ii) describing why this may occur, and (iii) providing the user with means to detect those cases so that trustworthiness is restored. In particular, we present a method for detecting risk scenarios for time-randomised caches, based on principles that apply to any other time-randomised resource which may challenge the application of MBPTA.
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