Tradeoff exploration between reliability, power consumption, and execution time for embedded systems

Abstract

For autonomous critical real-time embedded systems (e.g., satellite), guaranteeing a very high level of reliability is as important as keeping the power consumption as low as possible. We propose an off-line scheduling heuristic which, from a given software application graph and a given multiprocessor architecture (homogeneous and fully connected), produces a static multiprocessor schedule that optimizes three criteria: its length (crucial for real-time systems), its reliability (crucial for dependable systems), and its power consumption (crucial for autonomous systems). Our tricriteria scheduling heuristic, called TSH, uses the active replication of the operations and the data-dependencies to increase the reliability, and uses dynamic voltage and frequency scaling to lower the power consumption. We demonstrate the soundness of TSH. We also provide extensive simulation results to show how TSH behaves in practice: Firstly, we run TSH on a single instance to provide the whole Pareto front in 3D; Secondly, we compare TSH versus the ECS heuristic (Energy-Conscious Scheduling) from the literature; And thirdly, we compare TSH versus an optimal Mixed Linear Integer Program.

Building Correct Cyber-Physical Systems: Why We Need a Multiview Contract Theory

“…But, perhaps less known is the negative impact on the system's reliability, because lowering the voltage makes the system sensitive to noise and lower energy particles, which are likely to create a critical charge leading to a transient failure [44]. Here again, these intricate dependencies between the viewpoints call for integrated methods and tools, as in [39] for the timing, energy, and temperature viewpoints, or in [5] for the timing, energy, and reliability viewpoints.…”

Adaptive Mapping for Multiple Applications on Parallel Architectures

“…In this paper we use the approach presented in [9] which involves transforming all the criteria except one into constraints, and then minimizing the last remaining criterion iteratively and which is inspired from the ϵ-constraint method [10]. Figure 6 illustrates the particular case of two criteria Z 1 and Z 2 .…”

ERPOT: A Quad-Criteria Scheduling Heuristic to Optimize Execution Time, Reliability, Power Consumption and Temperature in Multicores

“…Considering these four criteria simultaneously during the design phase is very difficult because they are antagonistic [1], [2], [4]- [9]. For instance, the total execution time and reliability are antagonistic because increasing the reliability requires some form of redundancy (be it spatial or temporal), which negatively impacts the execution time.…”

“…Although several studies have addressed some of these parameters, none have considered these four criteria jointly in an optimization problem. For instance, some studies completely ignore the reliability [4], [14] or the temperature [2], [9]. Other studies tackle the problem as a hardware/software co-design problem, jointly optimizing the floorplan of the multicore and the schedule of the application task graph to minimize the peak temperature [14], but without considering the reliability.…”