Support for Managing the Survivability of Energy Systems Based on a Combinatorial Approach

Bychkov, Igor V.; Gorsky, Sergey; Edelev, Alexei; Kostromin, Roman; Sidorov, Ivan; Feoktistov, Alexander; Fereferov, E. S.; Fedorov, Roman K.

doi:10.1134/s1064230721060071

Cited by 2 publications

(1 citation statement)

References 27 publications

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“…Overall, our approach to GVA [49] integrates and develops the advantages of the approaches presented in [6,42]. In particular, we combine models of different energy systems to study their joint operation under extreme conditions.…”

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confidence: 99%

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

Feoktistov,

Edelev,

Tchernykh

et al. 2023

Computation

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Implementing high-performance computing (HPC) to solve problems in energy infrastructure resilience research in a heterogeneous environment based on an in-memory data grid (IMDG) presents a challenge to workflow management systems. Large-scale energy infrastructure research needs multi-variant planning and tools to allocate and dispatch distributed computing resources that pool together to let applications share data, taking into account the subject domain specificity, resource characteristics, and quotas for resource use. To that end, we propose an approach to implement HPC-based resilience analysis using our Orlando Tools (OT) framework. To dynamically scale computing resources, we provide their integration with the relevant software, identifying key application parameters that can have a significant impact on the amount of data processed and the amount of resources required. We automate the startup of the IMDG cluster to execute workflows. To demonstrate the advantage of our solution, we apply it to evaluate the resilience of the existing energy infrastructure model. Compared to similar approaches, our solution allows us to investigate large infrastructures by modeling multiple simultaneous failures of different types of elements down to the number of network elements. In terms of task and resource utilization efficiency, we achieve almost linear speedup as the number of nodes of each resource increases.

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confidence: 99%

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

Feoktistov,

Edelev,

Tchernykh

et al. 2023

Computation

View full text Add to dashboard Cite

show abstract

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-based Energy Infrastructure Resilience Studies

Feoktistov,

Edelev,

Tchernykh

et al. 2023

Preprint

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Implementing High-Performance Computing to solve In-Memory Data Grid (IMDG)-based energy infrastructure resilience research problems in a heterogeneous environment presents a challenge to workflow management systems. Large-scale energy infrastructure needs multi-variant planning and tools to allocate and dispatch resources in IMDG taking into account the subject domain specificity, resource characteristics, and constraints and quotas for resource use. To that end, we propose a workflow management system using our Orlando Tools framework. To scale computing resources, we provide their integration and use corresponding software to determine key application parameters that can significantly impact the processed data size and the required number of allocated resources. We automated the IMDG cluster launch for the workflow executions. To demonstrate the advantage of our solution, we apply it to evaluate the resilience of the existing energy infrastructure model. Compared to similar approaches, our approach explores large infrastructures by modeling many simultaneously failed elements of different types up to the number of network elements. In terms of problem-solving efficiency and resource use, we achieve near-linear speedup with increasing the number of nodes of each resource.

show abstract

Support for Managing the Survivability of Energy Systems Based on a Combinatorial Approach

Cited by 2 publications

References 27 publications

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-based Energy Infrastructure Resilience Studies

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