Topology Modeling and Analysis of a Power Grid Network Using a Graph Database

Kan, Bowen; Zhu, Wendong; Chen, Xi; Shi, Di; Yu, Woong‐Ryeol

doi:10.2991/ijcis.10.1.96

Cited by 19 publications

(10 citation statements)

References 16 publications

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“…According to Neo4j documentation, Neo4j is an opensource database written in Java and Scala, published under a dual model of free software and commercial license (Kan et al, 2017;Needham and Hodler, 2019;Jabri, 2020). It consists in implementing generic property graph models and providing complete database features, including Atomicity, Consistency, Isolation, Durability (ACID) transaction compliance, cluster support and execution failover.…”

Section: Neo4jmentioning

confidence: 99%

See 1 more Smart Citation

COV19-Dijkstra: A COVID-19 Propagation Model Based on Dijkstra’s Algorithm

Mavakala¹,

Adoni²,

Aoun³

et al. 2023

Journal of Computer Science

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The presence of the coronavirus, known as COVID-19, has prompted several researchers to study the mode of spread and the different defense mechanisms of the virus. As a reminder, obtaining a vaccine, for which much research is being conducted around the world, is a long and expensive process and it is unlikely that the pandemic can be treated in time. In this article, we present a new way to assess and limit the spread of the virus while trying to answer the following important questions: How to use the shortest path algorithm in a graph to analyze and better understand the spread of the virus? How to use the predictive power of the graph using the shortest path algorithm to find the relationships of a person who might be most at risk? The designed algorithm simulates how the virus spreads and infects people through the graph. Since the size of the collected COVID-19 data can reach a large volume over time and speaking of the graph concept, the NOSQL database including Neo4j which is a graph oriented NOSQL database is used for data collection, storage and processing. To enable the design and optimization of virus defense systems, this study proposes a feasible approach to quantify and predict the danger of a virus infection within a community.

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Section: Neo4jmentioning

confidence: 99%

“…4 on the Neo4j architecture, Neo4j stores graphic data in a number of different storage files. The main components of this architecture are its REST-based API, cache, transaction log and log files (Kan et al, 2017).…”

Section: Neo4jmentioning

confidence: 99%

COV19-Dijkstra: A COVID-19 Propagation Model Based on Dijkstra’s Algorithm

Mavakala¹,

Adoni²,

Aoun³

et al. 2023

Journal of Computer Science

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show abstract

“…Some related works have been conducted on the use of graph analytics and techniques in networking. Kan et al [11] demonstrated the effectiveness of modeling and analyzing power grid networks using a graph database. They presented an architecture for constructing a model for a power grid network utilizing the Neo4j database capabilities to analyze the network, such as shortest path search and conditional search.…”

Section: Related Workmentioning

confidence: 99%

BG-SDN: A Big Graph Framework for Topology Modeling and Traffic Analysis in Large-Scale SDN

Samaan

Jeiad

2022

Preprint

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This paper presented a new method of modeling a Software Defined Networking (SDN) network as a graph and importing traffic data into the created graph using graph techniques to speed up the computations required in traffic analysis and management. For this purpose, a specialized application named TMTA (Topology Modeling and Traffic Analysis) is created to model the SDN network topology as a graph and feed the created graph with traffic data. To achieve high performance, the TMTA application is integrated with the Neo4j graph database utilizing its ability to store and process big graphs consisting of massive amounts of highly interconnected data in a scalable and reliable manner. For performance evaluation, various sizes of network topologies ranging from 41 to 62,586 devices are modeled using the TMTA application and stored in Neo4j. Evaluation results show that the proposed big graph framework can handle large-scale topologies effectively and perform traffic analysis tasks, i.e., calculating the control score of each device in the network and finding the shortest path between devices in a very reasonable time.

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“…In Ref. [17], traditional relational databases (PostgreSQL) were compared with graph databases (Neo4j) in the analysis of power grid data. With experiments, they demonstrated a better performance of topology modeling and analysis using graph databases.…”

Section: Related Workmentioning

confidence: 99%

Graph Modeling for Efficient Retrieval of Power Network Model Change History

et al. 2021

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Power grids are constantly evolving, and data changes are increasing. Operational technology (OT) is controlled by IT technologies in smart grids, where changes in the physical world impose changes in the software data model, as well as the continuous generation of data points, resulting in time series datasets. The increased need for processing large amounts of data combined with requirements to maintain and increase overall performances has created a significant challenge for traditional database solutions and relational database models. The main idea of this paper was to find and propose a graph model that will allow the retrieval of historical connectivity in a reduced time complexity. Furthermore, the research question was addressed by evaluating three different approaches where the results provide a foundation for the proposed design guidelines related to optimizing graph-based databases for a modern smart grid system. The results of the experiments demonstrated reduced time complexities from 3 to 5 times depending on the typical industry usage patterns and the selected graph model. This suggests that the design decision may severely affect the outcome for given smart grid use cases when using historical features in OT technologies. Therefore, the main contribution of the research is the proposed guidelines on how to design an optimal graph model that satisfies the described smart grid requirements.

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Topology Modeling and Analysis of a Power Grid Network Using a Graph Database

Cited by 19 publications

References 16 publications

COV19-Dijkstra: A COVID-19 Propagation Model Based on Dijkstra’s Algorithm

COV19-Dijkstra: A COVID-19 Propagation Model Based on Dijkstra’s Algorithm

BG-SDN: A Big Graph Framework for Topology Modeling and Traffic Analysis in Large-Scale SDN

Graph Modeling for Efficient Retrieval of Power Network Model Change History

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