Abstract | ||
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ABSTRACTModern "self-driving'' service infrastructures consist of a diverse collection of distributed control components providing a broad spectrum of application- and network-centric functions. The complex and non-deterministic nature of these interactions leads to failures, ranging from subtle gray failures to catastrophic service outages, that are difficult to anticipate and repair. Our goal is to call attention to the need for formal understanding of dynamic service infrastructure control. We provide an overview of several incidents reported by large service providers as well as issues in a popular orchestration system, identifying key characteristics of the systems and their failures. We then propose a verification approach in which we treat abstract models of control components and the environment as parametric transition systems and leverage symbolic model checking to verify safety and liveness properties, or propose safe configuration parameters. Our preliminary experiments show that our approach is effective in analyzing complex failure scenarios with acceptable performance overhead. |
Year | DOI | Venue |
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2020 | 10.1145/3422604.3425949 | ACM SIGCOMM |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Bingzhe Liu | 1 | 2 | 1.05 |
Ali Kheradmand | 2 | 0 | 0.34 |
Matthew Caesar | 3 | 1 | 1.70 |
P. Brighten Godfrey | 4 | 2519 | 145.37 |