A Review of Watchdog Architectures and their Application to Cubesats

The push towards ”faster, better, cheaper” missions with an emphasis on design reuse has led to the popularity of COTS products that have traditionally relied upon custom software and hardware [22]. The motivation for moving towards COTS hardware is faster, cheaper and more powerful processors with lower power consumption compared to those available in rad hard versions [21]. While moving towards COTS components has many advantages, it also requires developing mechanisms to protect the components from radiation harsh environments which high altitude and space systems are subject to. There are two primary methods to deal with the effects of radiation on an embedded system. The first, fault avoidance, can be defined as using more robust or radiation hardened components to avoid single event upsets caused by cosmic rays [17] and other high energy particles. While this approach ensures system reliability, it does carry with it several disadvantages. Primarily, fault avoidance increases system power usage, costs and lead times while decreasing computational power. Power requirements cause a trade off between higher voltage components and faster system clocks. Power consumption rises as the components voltage increases and as the system clock increases in frequency. When components are selected that are not in high demand by markets such as the consumer electronics industry, the cost of the components rise due to a lack of demand which also has the effect of increasing the lead time of the components. The alternative method to fault avoidance is fault detection. Even the most robust fault avoidance systems will eventually have a fault [17]. While fault avoidance systems aim to increase the mean time of failure to beyond the mission life, fault detection methods detect when the fault occurs [17] in order to handle the fault and limit the system downtime. There are a number of advantages to fault tolerant systems such as low power consumption, increased computational power and decreased hardware costs. However