A Survey of Fault-Tolerance Techniques for Embedded Systems from the Perspective of Power, Energy, and Thermal Issues

The relentless technology scaling has provided a significant increase in processor performance, but on the other hand, it has led to adverse impacts on system reliability. In particular, technology scaling increases the processor susceptibility to radiation-induced transient faults. Moreover, technology scaling with the discontinuation of Dennard scaling increases the power densities, thereby temperatures, on the chip. High temperature, in turn, accelerates transistor aging mechanisms, which may ultimately lead to permanent faults on the chip. To assure a reliable system operation, despite these potential reliability concerns, fault-tolerance techniques have emerged. Specifically, fault-tolerance techniques employ some kind of redundancies to satisfy specific reliability requirements. However, the integration of fault-tolerance techniques into real-time embedded systems complicates preserving timing constraints. As a remedy, many task mapping/scheduling policies have been proposed to consider the integration of fault-tolerance techniques and enforce both timing and reliability guarantees for real-time embedded systems. More advanced techniques aim additionally at minimizing power and energy while at the same time satisfying timing and reliability constraints. Recently, some scheduling techniques have started to tackle a new challenge, which is the temperature increase induced by employing fault-tolerance techniques. These emerging techniques aim at satisfying temperature constraints besides timing and reliability constraints. This paper provides an in-depth survey of the emerging research efforts that exploit fault-tolerance techniques while considering timing, power/energy, and temperature from the real-time embedded systems’ design perspective. In particular, the task mapping/scheduling policies for fault-tolerance real-time embedded systems are reviewed and classified according to their considered goals and constraints. Moreover, the employed fault-tolerance techniques, application models, and hardware models are considered as additional dimensions of the presented classification. Lastly, this survey gives deep insights into the main achievements and shortcomings of the existing approaches and highlights the most promising ones

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

INCOBAT

Electro-mobility is considered as a key technology to achieve green mobility and fulfil tomorrow’s emission standards. However, different challenges still need to be faced to achieve comparable performances to conventional vehicles and finally obtain market acceptance. Two of these challenges are vehicle range and production costs. In that context, the aim of INCOBAT (October 2013 – December 2016) was to provide innovative and cost efficient battery management systems for next generation HV-batteries. INCOBAT proposes a platform concept that achieves cost reduction, reduced complexity, increased reliability and flexibility while at the same time reaching higher energy efficiency.• Very tight control of the cell function leading to a significant increase of the driving range of the FEV;• Radical cost reduction of the battery management system with respect to current solutions;• Development of modular concepts for system architecture and partitioning, safety, security, reliability as well as verification and validation, thus enabling efficient integration into different vehicle platforms. The INCOBAT project focused on the following twelve technical innovations grouped into four innovation groups, which are summarized in this book:• Customer needs and integration aspects• Transversal innovation• Technology innovation• Transversal innovatio

Software development of reconfigurable real-time systems : from specification to implementation

This thesis deals with reconfigurable real-time systems solving real-time tasks scheduling problems in a mono-core and multi-core architectures. The main focus in this thesis is on providing guidelines, methods, and tools for the synthesis of feasible reconfigurable real-time systems in a mono-processor and multi-processor architectures. The development of these systems faces various challenges particularly in terms of stability, energy consumption, response and blocking time. To address this problem, we propose in this work a new strategy of i) placement and scheduling of tasks to execute real-time applications on mono-core and multi-core architectures, ii) optimization step based on Mixed integer linear programming (MILP), and iii) guidance tool that assists designers to implement a feasible multi-core reconfigurable real-time from specification level to implementation level. We apply and simulate the contribution to a case study, and compare the proposed results with related works in order to show the originality of this methodology.Echtzeitsysteme laufen unter harten Bedingungen an ihre Ausführungszeit. Die Einhaltung der Echtzeit-Bedingungen bestimmt die Zuverlässigkeit und Genauigkeit dieser Systeme. Neben den Echtzeit-Bedingungen müssen rekonfigurierbare Echtzeitsysteme zusätzliche Rekonfigurations-Bedingungen erfüllen. Diese Arbeit beschäftigt sich mit rekonfigurierbaren Echtzeitsystemen in Mono- und Multicore-Architekturen. An die Entwicklung dieser Systeme sind verschiedene Anforderungen gestellt. Insbesondere muss die Rekonfigurierbarkeit beachtet werden. Dabei sind aber Echtzeit-Bedingungen und Ressourcenbeschränkungen weiterhin zu beachten. Darüber hinaus werden die Kosten für die Entwicklung dieser Systeme insbesondere durch falsche Designentscheidungen in den frühen Phasen der Entwicklung stark beeinträchtigt. Das Hauptziel in dieser Arbeit liegt deshalb auf der Bereitstellung von Handlungsempfehlungen, Methoden und Werkzeugen für die zielgerichtete Entwicklung von realisierbaren rekonfigurierbaren Echtzeitsystemen in Mono- und Multicore-Architekturen. Um diese Herausforderungen zu adressieren wird eine neue Strategie vorgeschlagen, die 1) die Funktionsallokation, 2) die Platzierung und das Scheduling von Tasks, 3) einen Optimierungsschritt auf der Basis von Mixed Integer Linear Programming (MILP) und 4) eine entscheidungsunterstützende Lösung umfasst, die den Designern hilft, eine realisierbare rekonfigurierbare Echtzeitlösung von der Spezifikationsebene bis zur Implementierungsebene zu entwickeln. Die vorgeschlagene Methodik wird auf eine Fallstudie angewendet und mit verwandten Arbeiten vergliche

A Survey of Research into Mixed Criticality Systems

This survey covers research into mixed criticality systems that has been published since Vestal’s seminal paper in 2007, up until the end of 2016. The survey is organised along the lines of the major research areas within this topic. These include single processor analysis (including fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, realistic models, and systems issues. The survey also explores the relationship between research into mixed criticality systems and other topics such as hard and soft time constraints, fault tolerant scheduling, hierarchical scheduling, cyber physical systems, probabilistic real-time systems, and industrial safety standards

Fundamentals

Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

INCOBAT

Electro-mobility is considered as a key technology to achieve green mobility and fulfil tomorrow’s emission standards. However, different challenges still need to be faced to achieve comparable performances to conventional vehicles and finally obtain market acceptance. Two of these challenges are vehicle range and production costs. In that context, the aim of INCOBAT (October 2013 – December 2016) was to provide innovative and cost efficient battery management systems for next generation HV-batteries. INCOBAT proposes a platform concept that achieves cost reduction, reduced complexity, increased reliability and flexibility while at the same time reaching higher energy efficiency.• Very tight control of the cell function leading to a significant increase of the driving range of the FEV;• Radical cost reduction of the battery management system with respect to current solutions;• Development of modular concepts for system architecture and partitioning, safety, security, reliability as well as verification and validation, thus enabling efficient integration into different vehicle platforms. The INCOBAT project focused on the following twelve technical innovations grouped into four innovation groups, which are summarized in this book:• Customer needs and integration aspects• Transversal innovation• Technology innovation• Transversal innovatio

Learning-based run-time power and energy management of multi/many-core systems: current and future trends

Multi/Many-core systems are prevalent in several application domains targeting different scales of computing such as embedded and cloud computing. These systems are able to fulfil the everincreasing performance requirements by exploiting their parallel processing capabilities. However, effective power/energy management is required during system operations due to several reasons such as to increase the operational time of battery operated systems, reduce the energy cost of datacenters, and improve thermal efficiency and reliability. This article provides an extensive survey of learning-based run-time power/energy management approaches. The survey includes a taxonomy of the learning-based approaches. These approaches perform design-time and/or run-time power/energy management by employing some learning principles such as reinforcement learning. The survey also highlights the trends followed by the learning-based run-time power management approaches, their upcoming trends and open research challenges

Scalability of broadcast performance in wireless network-on-chip

Networks-on-Chip (NoCs) are currently the paradigm of choice to interconnect the cores of a chip multiprocessor. However, conventional NoCs may not suffice to fulfill the on-chip communication requirements of processors with hundreds or thousands of cores. The main reason is that the performance of such networks drops as the number of cores grows, especially in the presence of multicast and broadcast traffic. This not only limits the scalability of current multiprocessor architectures, but also sets a performance wall that prevents the development of architectures that generate moderate-to-high levels of multicast. In this paper, a Wireless Network-on-Chip (WNoC) where all cores share a single broadband channel is presented. Such design is conceived to provide low latency and ordered delivery for multicast/broadcast traffic, in an attempt to complement a wireline NoC that will transport the rest of communication flows. To assess the feasibility of this approach, the network performance of WNoC is analyzed as a function of the system size and the channel capacity, and then compared to that of wireline NoCs with embedded multicast support. Based on this evaluation, preliminary results on the potential performance of the proposed hybrid scheme are provided, together with guidelines for the design of MAC protocols for WNoC.Peer ReviewedPostprint (published version