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Byzantine Fault Tolerance (BFT) is a classic technique for defending distributed systems against a wide range of faults and attacks. However, existing solutions are designed for systems where nodes can interact only by exchanging messages. They are not directly applicable to systems where nodes have sensors and actuators and can also interact in the physical world – perhaps by blocking each other’s path or by crashing into each other. In this paper, we take a first stab at extending BFT to this larger class of systems. We focus on multi-robot systems (MRS), an emerging technology that is increasingly being deployed for applications such as target tracking, warehouse logistics, and exploration. An MRS can consist of dozens of interacting robots and is thus a bona-fide distributed system. The classic masking guarantee is not practical in a MRS, but we propose a variant called bounded-time interaction that can be implemented, and we present an algorithm that achieves it, in combination with a few small hardware tweaks. We built a simulator and prototyped wheeled robots to show that our algorithm is effective, and that it has a reasonable overhead. 

Aerial vehicles with dozens of rotors are becoming increasingly common in important applications such as transportation and construction. One challenge with building such a system is to ensure that the system is robust against faults: as the number of rotors increases, the likelihood of a rotor failing during operation also increases; despite the spare thrust capacity provided by the redundant rotors, a rotor fault can significantly impact the motion and safety of the system. This paper presents an efficient fault detection and isolation (FDI) method for aerial vehicles with a large number of rotors. Our approach relies on two key insights: First, the effect of a faulty rotor directly affects the tracking error in roll and in pitch. This property can be used to order our faulty rotor search space. Second, the error in either roll or pitch is related to both the distance from the (relevant) axis and the severity of a fault. With these observations, we can use probe faults to isolate faulty rotors. Evaluation results show that our technique can efficiently detect and isolate faults in multi-rotor aerial vehicles with up to 64 rotors (8 more rotors than in existing FDI work), and that it can help improve robustness. To the best of our knowledge, our FDI method is the first that scales to several dozens of rotors. 

In contemporary database applications, the demand for memory resources is intensively high. To enhance adaptability to varying resource needs and improve cost efficiency, the integration of diverse storage technologies within heterogeneous memory architectures emerges as a promising solution. Despite the potential advantages, there exists a significant gap in research related to the security of data within these complex systems. This paper endeavors to fill this void by exploring the intricacies and challenges of ensuring data security in object-oriented heterogeneous memory systems. We introduce the concept of Unified Encrypted Memory (UEM) management, a novel approach that provides unified object references essential for data management platforms, while simultaneously concealing the complexities of physical scheduling from developers. At the heart of UEM lies the seamless and efficient integration of data encryption techniques, which are designed to ensure data integrity and guarantee the freshness of data upon access. Our research meticulously examines the security deficiencies present in existing heterogeneous memory system designs. By advancing centralized security enforcement strategies, we aim to achieve efficient object-centric data protection. Through extensive evaluations conducted across a variety of memory configurations and tasks, our findings highlight the effectiveness of UEM. The security features of UEM introduce low and acceptable overheads, and UEM outperforms conventional security measures in terms of speed and space efficiency.