Abstract
This work presents a Very Large Scale Integration (VLSI) design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and programmable PieceWise-Affine hyper-Rectangular (PWAR) model. An algorithm is presented to find the best values of the programmable parameters given a set of (empirical or simulated) input-output data. The VLSI design of the trusted virtual sensor uses the fast authenticated encryption algorithm, AEGIS, to ensure the integrity of the provided virtual measurement and to encrypt it, and a Physical Unclonable Function (PUF) based on a Static Random Access Memory (SRAM) to ensure the integrity of the sensor itself. Implementation results of a prototype designed in a 90-nm Complementary Metal Oxide Semiconductor (CMOS) technology show that the active silicon area of the trusted virtual sensor is 0.86 mm and its power consumption when trusted sensing at 50 MHz is 7.12 mW. The maximum operation frequency is 85 MHz, which allows response times lower than 0.25 s. As application example, the designed prototype was programmed to estimate the yaw rate in a vehicle, obtaining root mean square errors lower than 1.1%. Experimental results of the employed PUF show the robustness of the trusted sensing against aging and variations of the operation conditions, namely, temperature and power supply voltage (final value as well as ramp-up time).
Highlights
This work presents a Very Large Scale Integration (VLSI) design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption
PieceWise-Affine hyper-Rectangular (PWAR)-based models are selected since they are very suitable to be realized by programmable ICs that can be adjusted to different applications
This paper describes the VLSI design of trusted virtual sensors
Summary
A virtual sensor estimates the value of a variable that is very difficult or costly to measure physically by modelling the relation between that variable and others that can be measured with low-cost commercial sensors. The use of virtual sensors has increased continuously since the early 1980s in a wide number of industrial applications, such as building monitoring [1], robotics [2], process control [3,4], or automotive engineering [5]. PWAS-based virtual sensors are simpler to implement in FPGAs than neural-network-based sensors and provide higher computation speed, as shown in [10]. Circuit (IC) solution for virtual sensors is very interesting since it can provide a minimum unitary cost with high performance in terms of area, power and speed This is why this paper focuses on virtual sensor design into ICs. PWAR-based models are selected since they are very suitable to be realized by programmable ICs that can be adjusted to different applications. To solve the problem of data integrity, Message Authentication Codes (MACs) are usually employed.
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