Embryonic electronics: State of the art and future perspective

Qingqi, Zhuo; Ye, Qian; Li, Yue; Wang, Nantian; Tingpeng, Li

doi:10.1109/icemi.2013.6743098

Cited by 8 publications

(3 citation statements)

References 34 publications

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“…where P1, P2, P3, P4 = four digital input lines, G is universal quantification of the expression. Level_1 top control logic FC1, FC2 NOT, addition FC3, FC4 delay, OR FC5, FC6 multiplexing, subtraction Level_2 PI controller FC12, FC13 multiplication, addition FC14, FC17 FC15, FC16 comparison, multiplication FC7, FC8 multiplexing Level_3 bottom control logic FC9 delay FC10 addition FC11 subtraction [7,8,29,30]. Table 3 summarises the comparison results when implementing the EDG application with an array of N*N functional cells.…”

Section: Design Practices and Verification Methodsmentioning

confidence: 99%

“…Overhead Assessment In this section we perform a qualitative comparison of the proposed architecture and comparable systems found in the literature. These reference cases include a voting-bymajority Triple Modular Redundancy (TMR) w self-healing architecture, the re-routing self-healing architecture by Lala et al, and the self-healing architecture inspired by the endocrine cellular communication by Yang, I et al [29], [8], [30], [7]. Table 3 summarizes the comparison results when implementing the Emergency Diesel Generator (EDG) application with an array of N*N functional cells.…”

Section: Comparative Self-healing Capacity and Areamentioning

confidence: 99%

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Self‐repairing hardware architecture for safety‐critical cyber‐physical‐systems

Khairullah

Elks

2019

IET cyber-phys. syst.

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Digital embedded systems in safety-critical cyber-physical-systems require high levels of resilience and robustness against different fault classes. In recent years, self-healing concepts based on biological physiology have received attention for the design and implementation of reliable systems. However, many of these approaches have not been architected from the outset with safety in mind, nor have they been targeted for the safety-related automation industry where significant need exists. This paper presents a new self-healing hardware architecture inspired by integrating biological concepts, fault tolerance techniques, and IEC 61131-3 operational schematics to facilitate adaption in automation and critical infrastructure. The proposed architecture is organized in two levels: the critical functions layer used for providing the intended service of the application and the healing layer that continuously monitors the correct execution of that application and generates health syndromes to heal any failure occurrence inside the functions layer. Finally, two industrial applications have been mapped on this architecture to date and we believe the nexus of its concepts can positively impact the next generation of critical cyberphysical-systems in industrial automation.

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Section: Design Practices and Verification Methodsmentioning

confidence: 99%

Section: Comparative Self-healing Capacity and Areamentioning

confidence: 99%

Self‐repairing hardware architecture for safety‐critical cyber‐physical‐systems

Khairullah

Elks

2019

IET cyber-phys. syst.

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“…From the standpoint of cybernetics and computer science, bio-inspired self-repairing hardware can be considered as a reconfigurable system, which supports a dynamic arrangement of function blocks on the eCell array in response to the interference caused by faults. In this framework, the substitution process is a dynamic placement method where the placement evolves by a series of transitions at run time [7]. Current systems can only generate some predefined fault-free placements from a finite number of initial placements.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Placement Optimization for Bio-Inspired Self-Repairing Hardware

Liu

Xiao

et al. 2020

IEEE Access

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Bio-inspired self-repairing hardware is a distributed self-adaptive system, characterized by powerful fault-tolerant ability and environment adaptivity. However, it suffers from some difficulties such as large resource consumption and degraded circuit performances. From the viewpoint of cybernetics and computer science, the cellular differentiation and substitution process of bio-inspired self-repairing hardware can be converted into dynamic placement problems on a reconfigurable system. Current systems can only generate some predefined fault-free placements from a finite number of initial placements. The aim of this paper was to achieve high-quality placements from arbitrary initial placements. Based on P systems, an analysis has been made on the limitations of current systems and an improved computing system has been developed to achieve the ergodic property. Its computational power has been verified by a constructive proof. Moreover, centering on the problem how to improve the placement quality on a distributed platform, the optimization model, task allocation, optimization strategy, and membrane optimization algorithm have been designed and developed. The optimization performances were verified and the calculation amount was exhibited by experiments. Finally, it indicated by comparison that the proposed approach would reduce the resource consumption and maintain good circuit performances. INDEX TERMS Bio-inspired self-repairing hardware, dynamic placement optimization, P systems, computing model, membrane optimization algorithms.

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A Dynamical Evolution Approach to High Placement Performance and Low Fault-Tolerant Cost for Bio-Inspired Self-Repairing Hardware

Liu

2020

IEEE Access

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Bio-inspired self-repairing hardware is a reconfigurable system characterized by high fault-tolerant ability. To further increase the placement performance and reduce the fault-tolerant cost, a dynamical evolution approach to multi-objective dynamic placement is developed. A primary challenge for our study is computational complexity. Based on group theory, the computing task was divided on the dimensions of time and space to increase the utilization of online computing resources. By introducing the multi-step placement transformation, a discrete dynamical system model was built and the multi-objective dynamic placement was converted into a stability problem of constrained systems. In order to satisfy the dynamical requirements, an artificial particle system model was built and its evolution laws were verified by dynamic analysis. By simulating the evolution laws, a dynamical evolution algorithm was proposed, which could avoid large-scale iterative calculation used in the conventional optimization search algorithms. Experiments have shown that the dynamical evolution method could offer high placement performance with low fault-tolerant cost. Besides, it also has the advantage of high design flexibility since there is no initial placement constraint. INDEX TERMS Bio-inspired self-repairing hardware, dynamical evolution, placement performance, faulttolerant cost.

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Embryonic electronics: State of the art and future perspective

Cited by 8 publications

References 34 publications

Self‐repairing hardware architecture for safety‐critical cyber‐physical‐systems

Self‐repairing hardware architecture for safety‐critical cyber‐physical‐systems

Dynamic Placement Optimization for Bio-Inspired Self-Repairing Hardware

A Dynamical Evolution Approach to High Placement Performance and Low Fault-Tolerant Cost for Bio-Inspired Self-Repairing Hardware

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