Biblio

The coming generation of Internet-of-Things (IoT) applications will process massive amounts of incoming data while supporting data mining and online learning. In cases with demanding real-time requirements, such systems behave as smart memories: a high-bandwidth service that captures sensor input, processes it using machine-learning tools, replicates and stores "interesting" data (discarding uninteresting content), updates knowledge models, and triggers urgently-needed responses. Derecho is a high-throughput library for building smart memories and similar services. At its core Derecho implements atomic multicast (Vertical Paxos) and state machine replication (the classic durable Paxos). Derecho's replicated\textbackslashtextlessT\textbackslashtextgreater template defines a replicated type; the corresponding objects are associated with subgroups, which can be sharded into key-value structures. The persistent\textbackslashtextlessT\textbackslashtextgreater and volatile\textbackslashtextlessT\textbackslashtextgreater storage templates implement version vectors with optional NVM persistence. These support time-indexed access, offering lock-free snapshot isolation that blends temporal precision and causal consistency. Derecho automates application management, supporting multigroup structures and providing consistent knowledge of the current membership mapping. A query can access data from many shards or subgroups, and consistency is guaranteed without any form of distributed locking. Whereas many systems run consensus on the critical path, Derecho requires consensus only when updating membership. By leveraging an RDMA data plane and NVM storage, and adopting a novel receiver-side batching technique, Derecho can saturate a 12.5GB RDMA network, sending millions of events per second in each subgroup or shard. In a single subgroup with 2–16 members, through-put peaks at 16 GB/s for large (100MB or more) objects. While key-value subgroups would typically use 2 or 3-member shards, unsharded subgroups could be large. In tests with a 128-member group, Derecho's multicast and Paxos protocols were just 3–5x slower than for a small group, depending on the traffic pattern. With network contention, slow members, or overlapping groups that generate concurrent traffic, Derecho's protocols remain stable and adapt to the available bandwidth.

Modern applications often operate on data in multiple administrative domains. In this federated setting, participants may not fully trust each other. These distributed applications use transactions as a core mechanism for ensuring reliability and consistency with persistent data. However, the coordination mechanisms needed for transactions can both leak confidential information and allow unauthorized influence. By implementing a simple attack, we show these side channels can be exploited. However, our focus is on preventing such attacks. We explore secure scheduling of atomic, serializable transactions in a federated setting. While we prove that no protocol can guarantee security and liveness in all settings, we establish conditions for sets of transactions that can safely complete under secure scheduling. Based on these conditions, we introduce \textbackslashti\staged commit\, a secure scheduling protocol for federated transactions. This protocol avoids insecure information channels by dividing transactions into distinct stages. We implement a compiler that statically checks code to ensure it meets our conditions, and a system that schedules these transactions using the staged commit protocol. Experiments on this implementation demonstrate that realistic federated transactions can be scheduled securely, atomically, and efficiently.