Geoscience model service integrated workflow for rainstorm waterlogging analysis

Tan, Xicheng; Jiao, Jingguo; Chen, Nengcheng; Huang, Fang; Di, Liping; Wang, Jinchuan; Sha, Zongyao; Liu, Jin

doi:10.1080/17538947.2021.1898686

Cited by 10 publications

(2 citation statements)

References 69 publications

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“…For scientific applications focused on solving various classes of problems in the field of environmental monitoring, integration with geographic information systems through specialized Web processing services (WPSs) is of particular importance. Representative examples of projects aimed at creating and using such applications are the GeoJModel-Builder (GJMB) 2.0 [35] and Business Process Execution Language (BPEL) Designer Project (DP) 1.1.3 [36]. GJMB and BPEL DP belong to the class of WMSs.…”

Section: Workflow Management Systemsmentioning

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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Section: Workflow Management Systemsmentioning

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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show abstract

“…Unlike single processing services with limited capabilities, geospatial service chains implement multiple functions to meet users' needs. Users frequently composite multiple services into a service chain based on the relationship between services, commonly employed in the fields of hydrology [1][2][3][4] and the environment [5,6], resulting in value-added service [7].…”

Section: Introductionmentioning

confidence: 99%

An Augmented Geospatial Service Web Based on QoS Constraints and Geospatial Service Semantic Relationships

Jin

Liang

et al. 2022

IJGI

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The service network is capable of addressing large-scale service composition. However, existing service network works still have several limitations. Prior knowledge, such as expert-defined service chains, is not incorporated into the service network. QoS constraints are less considered in the service network, and thus the generated service chain does not always satisfy the optimal QoS constraints. Additionally, some basic services also require outputs to be used directly as inputs, which the service network cannot provide. To address these limitations, this paper proposes a geospatial service web (GSW) model named SR-QoS-GSW that incorporates service semantic relationships and QoS information. The SR-QoS-GSW model consists of atomic services and composite services that consider QoS, processing services, data services, and relationships among them. A SR-QoS-GSW prototype was developed using 570 atomic services and 27 composite services and evaluated using two case studies—a river network extraction and an urban housing selection. Then, the information entropy and time complexity between SR-QoS-GSW and the existing service network were compared. The results show that geospatial service chains can be created more efficiently by incorporating existing service chains as composite services. Integrating QoS information into the GSW would allow service composition algorithms to generate service chains that satisfy optimal QoS constraints. The outputs of services used as new inputs with additional self-matching relationships also give the service network greater flexibility. Finally, the analysis of the information entropy and time complexity verified the increased diversity and decreased the search space of the SR-QoS-GSW.

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HMS-REST v1.0: A plugin for the HEC-HMS model to provide RESTful services

Lin,

Zhang

et al. 2023

Environmental Modelling & Software

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Geoscience model service integrated workflow for rainstorm waterlogging analysis

Cited by 10 publications

References 69 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 Augmented Geospatial Service Web Based on QoS Constraints and Geospatial Service Semantic Relationships

HMS-REST v1.0: A plugin for the HEC-HMS model to provide RESTful services

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