Resilience through Automated Adaptive Configuration for Distribution and Replication
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916790930505728 |
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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 |