  Mixed-Criticality (MC) systems have recently been devised to address the
requirements of real-time systems in industrial applications, where the system
runs tasks with different criticality levels on a single platform. In some
workloads, a high-critically task might overrun and overload the system, or a
fault can occur during the execution. However, these systems must be
fault-tolerant and guarantee the correct execution of all high-criticality
tasks by their deadlines to avoid catastrophic consequences, in any situation.
Furthermore, in these MC systems, the peak power consumption of the system may
increase, especially in an overload situation and exceed the processor Thermal
Design Power (TDP) constraint. This may cause generating heat beyond the
cooling capacity, resulting the system stop to avoid excessive heat and halting
the processor. In this paper, we propose a technique for dependent
dual-criticality tasks in fault-tolerant multi-core MC systems to manage peak
power consumption and temperature. The technique develops a tree of possible
task mapping and scheduling at design-time to cover all possible scenarios and
reduce the low-criticality task drop rate in the high-criticality mode. At
run-time, the system exploits the tree to select a proper schedule according to
fault occurrences and criticality mode changes. Experimental results show that
the average task schedulability is 74.14% on average for the proposed method,
while the peak power consumption and maximum temperature are improved by 16.65%
and 14.9 C on average, respectively, compared to a recent work. In addition,
for a real-life application, our method reduces the peak power and maximum
temperature by up to 20.06% and 5 C, respectively, compared to a
state-of-the-art approach.
