Reliability-Aware Proactive Energy Management in Hard Real-Time Systems

2012 ◽  
pp. 215-225 ◽  
Author(s):  
Satyakiran Munaga ◽  
Francky Catthoor
Keyword(s):  
Energy Management ◽  
Ad Hoc ◽  
Failure Criteria ◽  
Worst Case ◽  
Time Control ◽  
Run Time ◽  
Cost Penalty ◽  
Hard Real Time ◽  
The Cost ◽  
Time Systems

Advanced technologies such as sub-45nm CMOS and 3D integration are known to have more accelerated and increased number of reliability failure mechanisms. Classical reliability assessment methodology, which assumes ad-hoc failure criteria and worst-case for all influencing dynamic aspects, is no longer viable in these technologies. In this paper, the authors advocate that managing temperature and reliability at run-time is necessary to overcome this reliability-wall without incurring significant cost penalty. Nonlinear nature of modern systems, however, makes the run-time control very challenging. The authors suggest that full cost-consciousness requires a truly proactive controller that can efficiently manage system slack with future in perspective. This paper introduces the concept of “gas-pedal,” which enhances the effectiveness of the proactive controller in minimizing the cost without sacrificing the hard guarantees required by the constraints. Reliability-aware dynamic energy management of a processor running AVC motion compensation task is used as a motivational case study to illustrate the proposed concepts.

Reliability-Aware Proactive Energy Management in Hard Real-Time Systems

2010 ◽  
Vol 1 (4) ◽  
pp. 1-11
Author(s):  
Satyakiran Munaga ◽  
Francky Catthoor
Keyword(s):  
Energy Management ◽  
Ad Hoc ◽  
Failure Criteria ◽  
Worst Case ◽  
Time Control ◽  
Run Time ◽  
Cost Penalty ◽  
Hard Real Time ◽  
The Cost ◽  
Time Systems

Advanced technologies such as sub-45nm CMOS and 3D integration are known to have more accelerated and increased number of reliability failure mechanisms. Classical reliability assessment methodology, which assumes ad-hoc failure criteria and worst-case for all influencing dynamic aspects, is no longer viable in these technologies. In this paper, the authors advocate that managing temperature and reliability at run-time is necessary to overcome this reliability-wall without incurring significant cost penalty. Nonlinear nature of modern systems, however, makes the run-time control very challenging. The authors suggest that full cost-consciousness requires a truly proactive controller that can efficiently manage system slack with future in perspective. This paper introduces the concept of “gas-pedal,” which enhances the effectiveness of the proactive controller in minimizing the cost without sacrificing the hard guarantees required by the constraints. Reliability-aware dynamic energy management of a processor running AVC motion compensation task is used as a motivational case study to illustrate the proposed concepts.

A Method for Simultaneously Satisfying Important Constraints and Dependencies for Many Different Types of Processes in Embedded Real-Time Systems

2011 ◽  
Author(s):  
Jia Xu
Keyword(s):  
Real Time ◽  
Computation Time ◽  
Real Time Systems ◽  
Worst Case ◽  
Release Times ◽  
Different Types ◽  
High Assurance ◽  
Run Time ◽  
Soft Deadline ◽  
Time Systems

In most embedded, real-time applications, processes need to satisfy various important constraints and dependencies, such as release times, offsets, precedence relations, and exclusion relations. Embedded, real-time systems with high assurance requirements often must execute many different types of processes with such constraints and dependencies. Some of the processes may be periodic and some of them may be asynchronous. Some of the processes may have hard deadlines and some of them may have soft deadlines. For some of the processes, especially the hard real-time processes, complete knowledge about their characteristics can and must be acquired before run-time. For other processes, prior knowledge of their worst case computation time and their data requirements may not be available. It is important for many embedded real-time systems to be able to simultaneously satisfy as many important constraints and dependencies as possible for as many different types of processes as possible. In this paper, we discuss what types of important constraints and dependencies can be satisfied among what types of processes. We also present a method which guarantees that, for every process, no matter whether it is periodic or asynchronous, and no matter whether it has a hard deadline or a soft deadline, as long as the characteristics of that process are known before run-time, then that process will be guaranteed to be completed before predetermined time limits, while simultaneously satisfying many important constraints and dependencies with other processes.

Interactive WCET Prediction with Warning for Timeout Risk

2017 ◽  
Vol 31 (05) ◽  
pp. 1750012 ◽  
Author(s):  
Fanqi Meng ◽  
Xiaohong Su ◽  
Zhaoyang Qu
Keyword(s):  
Execution Time ◽  
Control Flow ◽  
Real Time Systems ◽  
Wcet Analysis ◽  
Running Speed ◽  
Worst Case ◽  
Worst Case Execution Time ◽  
Level Model ◽  
Hard Real Time ◽  
Time Systems

Worst case execution time (WCET) analysis is essential for exposing timeliness defects when developing hard real-time systems. However, it is too late to fix timeliness defects cheaply since developers generally perform WCET analysis in a final verification phase. To help developers quickly identify real timeliness defects in an early programming phase, a novel interactive WCET prediction with warning for timeout risk is proposed. The novelty is that the approach not only fast estimates WCET based on a control flow tree (CFT), but also assesses the estimated WCET with a trusted level by a lightweight false path analysis. According to the trusted levels, corresponding warnings will be triggered once the estimated WCET exceeds a preset safe threshold. Hence developers can identify real timeliness defects more timely and efficiently. To this end, we first analyze the reasons of the overestimation of CFT-based WCET calculation; then we propose a trusted level model of timeout risks; for recognizing the structural patterns of timeout risks, we develop a risk data counting algorithm; and we also give some tactics for applying our approach more effectively. Experimental results show that our approach has almost the same running speed compared with the fast and interactive WCET analysis, but it saves more time in identifying real timeliness defects.

Efficiently Handling Process Overruns and Underruns on Multiprocessors in Real-Time Embedded Systems

2017 ◽  
Author(s):  
Jia Xu
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Time Complexity ◽  
Multiprocessor System ◽  
Multiprocessor Systems ◽  
Worst Case ◽  
Real World Applications ◽  
Run Time ◽  
Hard Real Time ◽  
Time Overhead

In hard real-time and embedded multiprocessor system real-world applications, it is very important to strive to minimize the run-time overhead of the scheduler as much as possible, especially in hard real-time and embedded multiprocessor systems with limited processor and system resources. In this paper, we present a method that reduces the worst-case time complexity of the run-time scheduler for re-computing latest start times and for selecting processes for execution on a multiprocessor at run-time to O(n), where n is the number of processes.

An Overview of Worst-Case Execution Time Estimation for Embedded Programs

2014 ◽  
Vol 651-653 ◽  
pp. 624-629
Author(s):  
Liang Liang Kong ◽  
Lin Xiang Shi ◽  
Lin Chen
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Execution Time ◽  
Time Estimation ◽  
Worst Case ◽  
Performance Metric ◽  
Worst Case Execution Time ◽  
Hard Real Time ◽  
Time Systems

Most embedded systems are real-time systems, so real-time is an important performance metric for embedded systems. The worst-case execution time (WCET) estimation for embedded programs could satisfy the requirement of hard real-time evaluation, so it is widely used in embedded systems evaluation. Based on sufficient survey on the progress of WCET estimation around the world, it proposes a new classification of WCET estimation. After introducing the principle of WCET estimation, it mainly demonstrates various types of technologies to estimate WCET and classifies them into two main streams, namely, static and dynamic WCET estimations. Finally, it shows the development of WCET analysis tools.

scholarly journals Beyond the Traditional Analyses and Resource Management in Real-Time Systems

2022 ◽  
pp. 67-77
Author(s):  
Federico Reghenzani
Keyword(s):  
Real Time ◽  
Real Time Systems ◽  
Formal Proofs ◽  
Worst Case ◽  
Worst Case Execution Time ◽  
Quantitative Results ◽  
Real Time Applications ◽  
Hard Real Time ◽  
Phd Thesis ◽  
Time Systems

AbstractThe difficulties in estimating the Worst-Case Execution Time (WCET) of applications make the use of modern computing architectures limited in real-time systems. Critical embedded systems require the tasks of hard real-time applications to meet their deadlines, and formal proofs on the validity of this condition are usually required by certification authorities. In the last decade, researchers proposed the use of probabilistic measurement-based methods to estimate the WCET instead of traditional static methods. In this chapter, we summarize recent theoretical and quantitative results on the use of probabilistic approaches to estimate the WCET presented in the PhD thesis of the author, including possible exploitation scenarios, open challenges, and future directions.

Improving Fidelity of Energy Management Software Testing Through Hierarchical Clustering of Train Consist Data

2020 ◽  
Author(s):  
Bradford Aiken ◽  
Keith W. Wait
Keyword(s):  
New York ◽  
Energy Management ◽  
Clustering Algorithm ◽  
Ad Hoc ◽  
Fuel Efficiency ◽  
Test Cases ◽  
Real Time Control ◽  
Management Software ◽  
Energy Management Systems ◽  
Time Control

Abstract Energy management systems, such as New York Air Brake’s LEADER [1], are real-time control technologies that optimize train performance as Level 2 Autonomy systems under the SAE’s “Levels of Driving Automation” classification system [2], and are now commonly used by many railroads. Such systems require extensive testing due to varying requirements of speed and fuel efficiency, compatibility with the wide variation in consists actually marshalled in the field, as well as the potential for the systems to cause break-in-twos or other undesirable situations. Devising accurate test cases that translate well to real-world usage is a common obstacle in the software development process. Using empirical data gathered from sampling field observations and an unsupervised machine learning model, we have created a simple but effective software system capable of performing automated statistical analysis on train consists and recommending a small number of consists which best capture the variation observed on-track. The data produced by such a system is demonstrably useful in developing truly representative test cases for train control systems/energy management software. In this investigation, we first applied such an algorithm to a population of train consists from some arbitrary segment of North American track to identify the most representative sample. We then evaluated the performance of the LEADER driving strategy for the sample set of consists with one of two consists that had previously been used for ad-hoc development testing of the software. Our findings from these simulations indicate that the consists identified by the clustering algorithm display greater variation in LEADER-controlled performance across several features than the ad-hoc testing consists do. Such metrics are transit time, fuel consumption, speed limit adherence, and air brake usage. Application of the algorithm is therefore beneficial in that it allows for more efficient and more thorough testing and characterization of energy management software.

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