Related papers: Deployment Calculation and Analysis for a Fail-Ope…
The idle computers on a local area, campus area, or even wide area network represent a significant computational resource---one that is, however, also unreliable, heterogeneous, and opportunistic. This type of resource has been used…
This research presents a Python-based simulation framework designed to model electric vehicle (EV) on-demand transportation systems, with a focus on optimizing urban fleet operations. Built on a process-driven architecture, the system…
The importance of mission or safety critical software systems in many application domains of embedded systems is continuously growing, and so is the effort and complexity for reliability and safety analysis. Model driven development is…
A set of hardware in the loop simulation methods based on the UAV model is proposed to create fault data, which is used to judge the parts where faults happen. Actual flight experimental data is utilized to prove the reliability of Simulink…
Driving events, such as maneuvers at slow speed and turns, are important for durability assessments of vehicle components. By counting the number of driving events, one can estimate the fatigue damage caused by the same kind of events.…
Reliable prediction is an essential requirement for deep neural models that are deployed in open environments, where both covariate and semantic out-of-distribution (OOD) data arise naturally. In practice, to make safe decisions, a reliable…
The automotive domain is transitioning: vehicles act as rolling servers, persistently connected to numerous external entities. This connectivity, combined with rising on-board computing power for advanced driver assistance systems and…
As the complexity of software systems rises, methods for explaining their behaviour are becoming ever-more important. When a system fails, it is critical to determine which of its components are responsible for this failure. Within the…
Machine learning models commonly exhibit unexpected failures post-deployment due to either data shifts or uncommon situations in the training environment. Domain experts typically go through the tedious process of inspecting the failure…
Mobile inventory, mobile commerce, banking and/or commercial applications are some distinctive examples that increasingly use distributed transactions. It is inevitably harder to design efficient commit protocols, due to some intrinsic…
Achieving safety is a critical aspect of attaining autonomy in a platoon of autonomous vehicles. In this paper, we propose a distributionally robust risk framework to investigate cascading failures in platoons. To examine the impact of…
This paper proposes a novel model-based approach to combine the quantitative dependability (safety, reliability, availability, maintainability and IT security) analysis and trade-off analysis. The proposed approach is called DPN…
Although an ever-growing number of applications employ deep learning based systems for prediction, decision-making, or state estimation, almost no certification processes have been established that would allow such systems to be deployed in…
Real-time embedded platforms with resource constraints can take the benefits of mixed-criticality system where applications with different criticality-level share computational resources, with isolation in the temporal and spatial domain. A…
Internet supercomputing is an approach to solving partitionable, computation-intensive problems by harnessing the power of a vast number of interconnected computers. For the problem of using network supercomputing to perform a large…
Vehicle platoon often face the problem of lack of scalability of maneuvers in practical applications. Once a new scenario is added, the original program may no longer be available. To deal with this problem, this paper introduces a…
The emergence of intelligent, connected vehicles, containing complex functionality has potential to greatly benefit society by improving safety, security and efficiency of vehicular transportation. Much of this has been enabled by…
Resource selection and task placement for distributed execution poses conceptual and implementation difficulties. Although resource selection and task placement are at the core of many tools and workflow systems, the methods are ad hoc…
Distributed computing platforms provide a robust mechanism to perform large-scale computations by splitting the task and data among multiple locations, possibly located thousands of miles apart geographically. Although such distribution of…
The design of reliable circuits has received a lot of attention in the past, leading to the definition of several design techniques introducing fault detection and fault tolerance properties in systems for critical…