Composing Fault Tolerant In-Network Computing Systems via High-Level Intents
Ricardo Parizotto, Israat Haque, Alberto Egon Schaeffer-Filho · 2025
The performance benefits of data plane programmability have motivated many researchers to offload the computation of applications that previously operated only on servers to the network, creating the notion of in-network computing (INC). Because failures can occur in the data plane, fault tolerance mechanisms are essential for INC. However, INC operators and developers must manually set fault tolerance requirements using domain knowledge to change the source code. These manually set requirements may take time and lead to errors in case of misconfiguration. In this work, we present ARAUCARIA, a system that composes fault tolerance building blocks for INC based on high-level intents. The system allows the specification of requirements using an intent language, which allows the expression of consistency and availability requirements in a constrained natural language. A refinement process translates the intent and instruments the INC with essential building blocks and configurations. Our prototype of ARAUCARIA enables fault tolerance for INC applications on BMv2 and in a testbed with Tofino ASICs. Experiments show that the system provides fault tolerance with negligible overhead.