Conflict-free replicated data types (CRDTs) are highly available and performant data replication solutions for distributed applications. However, their eventual consistency guarantees are often insufficient for ensuring application correctness, especially in the presence of Byzantine failures. Naively applying traditional consensus and Byzantine fault tolerance (BFT) protocols to CRDT updates for stronger guarantees, while intuitive, negates the performance benefits of CRDTs. We introduce a novel programming model called reliable CRDTs that expands CRDTs with additional guarantees: users can query strongly or eventually consistent values, enforce a total order among selected operations, and define data-type level invariants while remaining operational in the presence of Byzantine failures. Reliable CRDTs enable the use of CRDTs in scenarios where strong consistency is needed while maintaining their performance advantages. We present an implementation of reliable CRDTs named Janus. It enhances CRDTs with the aforementioned features by functioning as a middleware that facilitates CRDT communication and asynchronously runs a BFT consensus protocol. Our evaluation demonstrates that Janus achieves 21× higher throughput than naively applying state-of-the-art BFT protocols such as HotStuff achieves, and it remains responsive even under heavy loads.

Existing permissioned blockchains often rely on coordination-based consensus protocols to ensure the safe execution of applications in a Byzantine environment. Furthermore, the protocols serialize the transactions by ordering them in a global order. The serializ-ability preserves the correctness of the application's state stored on the blockchain. However, coordination-based protocols limit the throughput and scalability and induce high latency. In contrast, application-level correctness requirements exist that are not dependent on the order of transactions, known as invariant-confluence (I-confluence). The I-confluent applications can execute transactions in a coordination-free manner, benefiting from the improved scalability compared to the coordination-based approaches. The safety and liveness of I-confluent applications are studied in non-Byzantine environments, but the correct execution of such applications remains a challenge in Byzantine coordination-free environments. We introduce OrderlessChain, a novel permissioned blockchain based on a novel BFT coordination-free protocol for the safe and live execution of I-confluent applications in a Byzantine environment. We implemented a prototype of our system, and our evaluation results show that our coordination-free approach performs significantly better than coordination-based blockchains.

Distribution System Operators (DSOs) face several challenges in managing comprehensive and up-to-date models of distribution grids. To address these problems, we propose a crowdsourcing framework for collecting grid devices. We also provide an inference approach for generating topological models of the distribution grids. Since distribution cables are often underground, we use spatial data analytics on the collected data in combination with other open data sources to infer the topology of the distribution grid. Additionally, to increase the quality of crowdsourced data, we propose a cost-effective approach for collecting and detecting grid elements in urban areas using commercial drones with an RGB camera. To evaluate our approach, we organized a crowdsourcing campaign to map and infer a district in Munich, Germany. The results are compared with the ground truth of the distribution system operator. Our results report a precision of up to 82 percent and a recall of up to 65 percent for the correctly crowdsourced grid devices. We also observe that the inferred models achieve a power length accuracy of 88 percent compared to the ground truth. We evaluated the detection of solar panels from aerial imagery by conducting field experiments, showing precision and recall levels of 68 and 69 percent, respectively.

With the increased adaption of blockchain technologies, permissioned blockchains such as Hyperledger Fabric provide a robust ecosystem for developing production-grade decentralized applications. However, the additional latency between executing and committing transactions, due to Fabric's three-phase transaction lifecycle of Execute-Order-Validate (EOV), is a potential scalability bottleneck. The added latency increases the probability of concurrent updates on the same keys by different transactions, leading to transaction failures caused by Fabric's concurrency control mechanism. The transaction failures increase the application development complexity and decrease Fabric's throughput. Conflict-free Replicated Datatypes (CRDTs) provide a solution for merging and resolving conflicts in the presence of concurrent updates. In this work, we introduce FabricCRDT, an approach for integrating CRDTs to Fabric. Our evaluations show that in general, FabricCRDT offers higher throughput of successful transactions than Fabric, while successfully committing and merging all conflicting transactions without any failures.