Adaptive reconfigurable voting for enhanced reliability in medium-grained fault tolerant architectures

Veljković, Filip; Riesgo, Teresa; Torre, Eduardo de la

doi:10.1109/ahs.2015.7231165

Cited by 8 publications

(9 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, IoT devices are exposed to various risks in a variety of environments, resulting in less stability. Technology research to maintain IoT has been conducted in many fields; for example, such research mainly uses techniques that compare processing results, using the duplicate and comparison technique for critical areas of hardware, and add redundancy circuits through voting techniques that maintain reliability [ 25 , 26 , 27 ]. In addition to the technology that uses hardware, the technology that uses software has developed as well.…”

Section: Methodsmentioning

confidence: 99%

mIoT: Metamorphic IoT Platform for On-Demand Hardware Replacement in Large-Scaled IoT Applications

Lee

Moon

et al. 2020

Sensors

View full text Add to dashboard Cite

As the Internet of Things (IoT) is becoming more pervasive in our daily lives, the number of devices that connect to IoT edges and data generated at the edges are rapidly increasing. On account of the bottlenecks in servers, due to the increase in data, as well as security and privacy issues, the IoT paradigm has shifted from cloud computing to edge computing. Pursuant to this trend, embedded devices require complex computation capabilities. However, due to various constraints, edge devices cannot equip enough hardware to process data, so the flexibility of operation is reduced, because of the limitations of fixed hardware functions, relative to cloud computing. Recently, as application fields and collected data types diversify, and, in particular, applications requiring complex computation such as artificial intelligence (AI) and signal processing are applied to edges, flexible processing and computation capabilities based on hardware acceleration are required. In this paper, to meet these needs, we propose a new IoT platform, called a metamorphic IoT (mIoT) platform, which can various hardware acceleration with limited hardware platform resources, through on-demand transmission and reconfiguration of required hardware at edges instead of via transference of sensing data to a server. The proposed platform reconfigures the edge’s hardware with minimal overhead, based on a probabilistic value, known as callability. The mIoT consists of reconfigurable edge devices based on RISC-V architecture and a server that manages the reconfiguration of edge devices based on callability. Through various experimental results, we confirmed that the callability-based mIoT platform can provide the hardware required by the edge device in real time. In addition, by performing various functions with small hardware, power consumption, which is a major constraint of IoT, can be reduced.

show abstract

Section: Methodsmentioning

confidence: 99%

mIoT: Metamorphic IoT Platform for On-Demand Hardware Replacement in Large-Scaled IoT Applications

Lee

Moon

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…. The output c v carries the current three active RTRPs as a tuple, such as in (8). The behavior of the Control Device regarding the output c v is modeled as follows.…”

Section: Votermentioning

confidence: 99%

“…Another application of TMR using RTR is presented by [8], where an adaptive reconfigurable voting mechanism whose main goal is to extend the dynamic and partial reconfiguration SEU mitigation to the voter, which is usually the single point of failure in TMR architectures.…”

Section: Related Workmentioning

confidence: 99%

Triple Modular Redundancy based on Runtime Reconfiguration and Formal Models of Computation

Bonna

Loubach

Sander

et al. 2019

Proceedings of the 10th Aerospace Technology Congress, October 8-9, 2019, Stockholm, Sweden

View full text Add to dashboard Cite

Runtime reconfiguration is one promising way to mitigate for increased failure rate and thereby it fulfills safety requirements needed for future safety-critical avionics systems. In case of a hardware fault, the system is able, during runtime, to automatically detect such fault and redirect the functionality from the defective module to a new safe reconfigured module, thus minimizing the effects of hardware faults. This paper introduces a high level abstraction architecture for safety-critical systems with runtime reconfiguration using the triple modular redundancy and the synchronous model of computation. A modeling strategy to be used in the design phase supported by formal models of computation is also addressed in the paper. The triple modular redundancy technique is used for detecting faults where, in case of inconsistency in one of the three processors caused by a fault, a new processor is reconfigured based on a software or hardware reconfiguration, and it assumes the tasks of the faulty processor. The introduced strategy considers that no other fault occurs during the reconfiguration of a new processor.

show abstract

“…A number of publications report on techniques that have been developed to decrease the MTTD and correct configuration memory errors in FPGA-based systems with a view to improve system reliability. These techniques are based either on TMR-MER [6,9,10,[16][17][18] or on scrubbing [19][20][21][22][23].…”

Section: Related Workmentioning

confidence: 99%

Scheduling configuration memory error checks to improve the reliability of FPGA‐based systems

Nguyen

Cetin²,

Diessel³

2018

IET Computers & Digital Techniques

View full text Add to dashboard Cite

Field-programmable gate arrays are susceptible to radiation-induced single event upsets. These are commonly dealt with using triple modular redundancy (TMR) and module-based configuration memory error recovery (MER). By triplicating components and voting on their outputs, TMR helps localise configuration memory errors, and by reconfiguring faulty components, MER swiftly corrects them. However, the order in which TMR voters are checked inevitably impacts the overall system reliability. In this study, the authors outline an approach for computing the reliability of TMR-MER systems that consist of finitely many components. They demonstrate that system reliability is improved when the more vulnerable components are checked more frequently than when they are checked in round-robin order. They propose a genetic algorithm for finding a voter checking schedule that maximises the reliability of TMR-MER systems. Results indicate that the mean time to failure (MTTF) of these systems can be increased by up to 400% when variable-rate voter checking (VRVC) is used instead of round robin. They show that VRVC achieves 15-23% increase in MTTF with a 10× reduction in checking frequency to reduce system power. They also found that VRVC detects errors 44% faster on average than round robin. Nomenclature Symbol Definition N number of TMR components in the system Ck component k, k = 1, …, N O kn Ck is observed for the nth time by checking its voter(s) Δt o time period between successive voter observations (assumed to be constant for a given system setting) Δt dk time period between two consecutive observations of Ck Δt rk time period to recover a faulty module of Ck Δt k total time period over which Ck can fail Δt di j time period between successive observations of Ci and Cj Δt d′i j average time period between two consecutive observations of Ci in the interval between two consecutive observations of Cj IET Comput. Digit. Tech.

show abstract

Adaptive reconfigurable voting for enhanced reliability in medium-grained fault tolerant architectures

Cited by 8 publications

References 25 publications

mIoT: Metamorphic IoT Platform for On-Demand Hardware Replacement in Large-Scaled IoT Applications

mIoT: Metamorphic IoT Platform for On-Demand Hardware Replacement in Large-Scaled IoT Applications

Triple Modular Redundancy based on Runtime Reconfiguration and Formal Models of Computation

Scheduling configuration memory error checks to improve the reliability of FPGA‐based systems

Contact Info

Product

Resources

About