Resilience through Automated Adaptive Configuration for Distribution and Replication

Fuente: arXiv
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Main Authors: Stoller, Scott D., Jayasankar, Balaji, Liu, Yanhong A.
Format: Preprint
Published: 2025
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author Stoller, Scott D.
Jayasankar, Balaji
Liu, Yanhong A.
author_facet Stoller, Scott D.
Jayasankar, Balaji
Liu, Yanhong A.
contents This paper presents a powerful automated framework for making complex systems resilient under failures, by optimized adaptive distribution and replication of interdependent software components across heterogeneous hardware components with widely varying capabilities. A configuration specifies how software is distributed and replicated: which software components to run on each computer, which software components to replicate, which replication protocols to use, etc. We present an algorithm that, given a system model and resilience requirements, (1) determines initial configurations of the system that are resilient, and (2) generates a reconfiguration policy that determines reconfiguration actions to execute in response to failures and recoveries. This model-finding algorithm is based on state-space exploration and incorporates powerful optimizations, including a quotient reduction based on a novel equivalence relation between states. We present experimental results from successfully applying a prototype implementation of our framework to a model of an autonomous driving system.
format Preprint
id arxiv_https___arxiv_org_abs_2506_10248
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Resilience through Automated Adaptive Configuration for Distribution and Replication
Stoller, Scott D.
Jayasankar, Balaji
Liu, Yanhong A.
Distributed, Parallel, and Cluster Computing
This paper presents a powerful automated framework for making complex systems resilient under failures, by optimized adaptive distribution and replication of interdependent software components across heterogeneous hardware components with widely varying capabilities. A configuration specifies how software is distributed and replicated: which software components to run on each computer, which software components to replicate, which replication protocols to use, etc. We present an algorithm that, given a system model and resilience requirements, (1) determines initial configurations of the system that are resilient, and (2) generates a reconfiguration policy that determines reconfiguration actions to execute in response to failures and recoveries. This model-finding algorithm is based on state-space exploration and incorporates powerful optimizations, including a quotient reduction based on a novel equivalence relation between states. We present experimental results from successfully applying a prototype implementation of our framework to a model of an autonomous driving system.
title Resilience through Automated Adaptive Configuration for Distribution and Replication
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2506.10248