Mixed-Criticality (MC) systems have emerged as an effective solution in various industries, where multiple tasks with various real-time and safety requirements (different levels of criticality) are integrated onto a common hardware platform. In these systems, a fault may occur due to different reasons, e.g., hardware defects, software errors or the arrival of unexpected events. In order to tolerate faults in MC systems, the re-execution technique is typically employed, which may lead to overrun of highcriticality tasks (HCTs), which necessitates the drop of low-criticality tasks (LCTs) or degrading their quality. However, frequent drops or relatively long execution times of LCTs (especially mission-critical tasks) are not always desirable and it may impose a negative impact on the performance, or the functionality of MC systems. In this regard, this paper proposes a realistic MC task model and develops a design-time task-drop aware schedulability analysis based on the Earliest Deadline First with Virtual Deadline (EDF-VD) algorithm. According to this analysis and the proposed scheduling policy based on the new MC task model, in the high-criticality (HI) mode, when an HCT overruns and the system switches to the HI mode, the number of drops per LCT is prohibited from passing a predefined threshold. In addition, to guarantee the real-time constraints and safety requirements of MC tasks in the presence of faults (assuming transient faults in this paper), a corresponding scheduling mechanism has been developed. According to the obtained results from an extensive set of simulations, which have been validated through a realistic avionic application, the proposed method improves the acceptance ratio by up to 43.9% compared to state-of-the-art.

No abstract

No abstract

With the widespread use of IoT applications and the increasing trend in the number of connected smart devices, the concept of routing has become very challenging. In this regard, the IPv6 Routing Protocol for Low-power and Lossy Networks (PRL) was standardized to be adopted in IoT networks. Nevertheless, while mobile IoT domains have gained significant popularity in recent years, since RPL was fundamentally designed for stationary IoT applications, it could not well adjust with the dynamic fluctuations in mobile applications. While there have been a number of studies on tuning RPL for mobile IoT applications, but still there is a high demand for more efforts to reach a standard version of this protocol for such applications. Accordingly, in this survey, we try to conduct a precise and comprehensive experimental study on the impact of various mobility models on the performance of a mobility-aware RPL to help this process. In this regard, a complete and scrutinized survey of the mobility models has been presented to be able to fairly justify and compare the outcome results. A significant set of evaluations has been conducted via precise IoT simulation tools to monitor and compare the performance of the network and its IoT devices in mobile RPL-based IoT applications under the presence of different mobility models from different perspectives including power consumption, reliability, latency, and control packet overhead. This will pave the way for researchers in both academia and industry to be able to compare the impact of various mobility models on the functionality of RPL, and consequently to design and implement application-specific and even a standard version of this protocol, which is capable of being employed in mobile IoT applications.