Probabilistic, Resource-Aware, Asynchronous, Out-of-Order Choreographies

2026-06-11

AI Summary

Existing formal methods struggle to quantify the likelihood and latency of asynchronous, out-of-order orchestrations or effectively assess how resources—such as communication delays, computational overhead, and fault recovery—affect system behavior. This work proposes AsInst, a novel orchestration language that, for the first time, integrates probabilistic and temporal resource awareness into semantic modeling. It employs temporal Bayesian networks to capture runtime values and their availability times, and establishes semantic equivalence with Future-based network semantics. The approach enables joint analysis of execution likelihood and performance, supports Ozone-style selective merge constructs, and has been successfully applied to communication fault recovery and runtime performance prediction, demonstrating its effectiveness in evaluating latency and reliability.

Abstract

Futures-based implementations of out-of-order choreographies can substantially improve latency and throughput, but their actual behavior depends on resources such as communication delay, computation time, failures, and recovery. Existing formal models such as Ozone's O3 describe which executions are possible, but do not directly explain how likely those executions are or how long they take. In this work we present AsInst, a probabilistic, resource-aware language for modeling the semantics of asynchronous choreographies with out-of-order execution. AsInst programs are interpreted as temporal Bayesian networks that model both the values produced at runtime and the times at which they become available. We prove that this central semantics correctly captures a corresponding futures-style network semantics. We also show that AsInst can encode Ozone-style select-and-merge conditionals, and we use case studies to model communication-failure recovery and analyze runtime performance.

Problem

• probabilistic
• resource-aware
• asynchronous choreographies
• out-of-order execution
• temporal semantics

Innovation

• probabilistic choreographies
• resource-aware modeling
• asynchronous out-of-order execution
• temporal Bayesian networks
• futures-based semantics