Static analysis of SEU effects on software applications

Control flow errors have been widely addressed in literature as a possible threat to the dependability of computer systems, and many clever techniques have been proposed to detect and tolerate them. Nevertheless, it has never been discussed if the overheads introduced by many of these techniques are justified by a reasonable probability of incurring control flow errors. This paper presents a static executable code analysis methodology able to compute, depending on the target microprocessor platform, the upper-bound probability that a given application incurs in a control flow error

Evolvable Embryonics: 2-in-1 Approach to Self-healing Systems

This paper covers the authors’ recent research in the area of evolutionary design optimisation in electronic application domain (Evolvable Hardware). This will be also presented in the context of biologically inspired systems where Evolvable Hardware is concerned with evolutionary synthesis of self-healing systems and potentially hardware capable of online adaptation to dynamically changing environment. We will also illustrate how EAs can produce novel and unintuitive design solutions, and possibly new design principles. The novelty of this research project addresses this compelling change in the traditional landscape of the associated research disciplines by seeking to provide a novel biologically inspired mechanism to support the design optimisation of self-healing architectures, that is Evolvable-Embryonics

Use of Field Programmable Gate Array Technology in Future Space Avionics

Fulfilling NASA's new vision for space exploration requires the development of sustainable, flexible and fault tolerant spacecraft control systems. The traditional development paradigm consists of the purchase or fabrication of hardware boards with fixed processor and/or Digital Signal Processing (DSP) components interconnected via a standardized bus system. This is followed by the purchase and/or development of software. This paradigm has several disadvantages for the development of systems to support NASA's new vision. Building a system to be fault tolerant increases the complexity and decreases the performance of included software. Standard bus design and conventional implementation produces natural bottlenecks. Configuring hardware components in systems containing common processors and DSPs is difficult initially and expensive or impossible to change later. The existence of Hardware Description Languages (HDLs), the recent increase in performance, density and radiation tolerance of Field Programmable Gate Arrays (FPGAs), and Intellectual Property (IP) Cores provides the technology for reprogrammable Systems on a Chip (SOC). This technology supports a paradigm better suited for NASA's vision. Hardware and software production are melded for more effective development; they can both evolve together over time. Designers incorporating this technology into future avionics can benefit from its flexibility. Systems can be designed with improved fault isolation and tolerance using hardware instead of software. Also, these designs can be protected from obsolescence problems where maintenance is compromised via component and vendor availability.To investigate the flexibility of this technology, the core of the Central Processing Unit and Input/Output Processor of the Space Shuttle AP101S Computer were prototyped in Verilog HDL and synthesized into an Altera Stratix FPGA

Advanced flight control system study

A fly by wire flight control system architecture designed for high reliability includes spare sensor and computer elements to permit safe dispatch with failed elements, thereby reducing unscheduled maintenance. A methodology capable of demonstrating that the architecture does achieve the predicted performance characteristics consists of a hierarchy of activities ranging from analytical calculations of system reliability and formal methods of software verification to iron bird testing followed by flight evaluation. Interfacing this architecture to the Lockheed S-3A aircraft for flight test is discussed. This testbed vehicle can be expanded to support flight experiments in advanced aerodynamics, electromechanical actuators, secondary power systems, flight management, new displays, and air traffic control concepts

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

A run time adaptive architecture to trade-off performance for fault tolerance applied to a DVB on-board processor

Reliability is one of the key issues in space applications. Although highly flexible and generally less expensive than predominantly used ASICs, SRAM-based FPGAs are very susceptible to radiation effects. Hence, various fault tolerant techniques have to be applied in order to handle faults and protect the design. This paper presents a reconfigurable on-board processor capable of run-time adaptation to harsh environmental conditions and different functional demands. Run-time reconfigurability is achieved applying two different reconfiguration methodologies. We propose a novel self-reconfigurable architecture able to on demand duplicate or triplicate part of the design in order to form DMR and TMR structures. Moreover, we introduce two different approaches for voting the correct output. The first one is a traditional voter that adapts to different DMR/TMR domain positions whereas the second implies comparing the captured flip-flop values directly from the configuration memory read through ICAP. The comparison is done periodically by an embedded processor thus completely excluding the voting mechanism in hardware. The proposed run-time reconfiguration methodology provides savings in terms of device utilization, reconfiguration time, power consumption and significant reductions in the amount of rad-hard memory used by partial configurations

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

An Adaptive Modular Redundancy Technique to Self-regulate Availability, Area, and Energy Consumption in Mission-critical Applications

As reconfigurable devices\u27 capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing environments that require high degree of adaptation. The hardware layer is implemented on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA) to provide self-repair using a novel approach called a Reconfigurable Adaptive Redundancy System (RARS). The software layer supervises the organic activities within the FPGA and extends the self-healing capabilities through application-independent, intrinsic, evolutionary repair techniques to leverage the benefits of dynamic Partial Reconfiguration (PR). A SMART prototype is evaluated using a Sobel edge detection application. This prototype is shown to provide sustainability for stressful occurrences of transient and permanent fault injection procedures while still reducing energy consumption and area requirements. An Organic Genetic Algorithm (OGA) technique is shown capable of consistently repairing hard faults while maintaining correct edge detector outputs, by exploiting spatial redundancy in the reconfigurable hardware. A Monte Carlo driven Continuous Markov Time Chains (CTMC) simulation is conducted to compare SMART\u27s availability to industry-standard Triple Modular Technique (TMR) techniques. Based on nine use cases, parameterized with realistic fault and repair rates acquired from publically available sources, the results indicate that availability is significantly enhanced by the adoption of fast repair techniques targeting aging-related hard-faults. Under harsh environments, SMART is shown to improve system availability from 36.02% with lengthy repair techniques to 98.84% with fast ones. This value increases to five nines (99.9998%) under relatively more favorable conditions. Lastly, SMART is compared to twenty eight standard TMR benchmarks that are generated by the widely-accepted BL-TMR tools. Results show that in seven out of nine use cases, SMART is the recommended technique, with power savings ranging from 22% to 29%, and area savings ranging from 17% to 24%, while still maintaining the same level of availability

A deep reinforcement learning based homeostatic system for unmanned position control

Deep Reinforcement Learning (DRL) has been proven to be capable of designing an optimal control theory by minimising the error in dynamic systems. However, in many of the real-world operations, the exact behaviour of the environment is unknown. In such environments, random changes cause the system to reach different states for the same action. Hence, application of DRL for unpredictable environments is difficult as the states of the world cannot be known for non-stationary transition and reward functions. In this paper, a mechanism to encapsulate the randomness of the environment is suggested using a novel bio-inspired homeostatic approach based on a hybrid of Receptor Density Algorithm (an artificial immune system based anomaly detection application) and a Plastic Spiking Neuronal model. DRL is then introduced to run in conjunction with the above hybrid model. The system is tested on a vehicle to autonomously re-position in an unpredictable environment. Our results show that the DRL based process control raised the accuracy of the hybrid model by 32%.N/