Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain Networks
This paper investigates the application of graph theory and variants of greedy graph coloring algorithms for the optimization of distributed peer-to-peer networks, with a special focus on private blockchain networks. The graph coloring problem, as an NP-hard problem, presents a challenge in determin...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Technologies |
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| Online Access: | https://www.mdpi.com/2227-7080/13/1/33 |
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| author | Miljenko Švarcmajer Denis Ivanović Tomislav Rudec Ivica Lukić |
| author_facet | Miljenko Švarcmajer Denis Ivanović Tomislav Rudec Ivica Lukić |
| author_sort | Miljenko Švarcmajer |
| collection | DOAJ |
| description | This paper investigates the application of graph theory and variants of greedy graph coloring algorithms for the optimization of distributed peer-to-peer networks, with a special focus on private blockchain networks. The graph coloring problem, as an NP-hard problem, presents a challenge in determining the minimum number of colors needed to efficiently allocate resources within the network. The paper deals with the influence of different graph density, i.e., the number of links, on the efficiency of greedy algorithms such as DSATUR, Descending, and Ascending. Experimental results show that increasing the number of links in the network contributes to a more uniform distribution of colors and increases the resistance of the network, whereby the DSATUR algorithm achieves the most uniform color saturation. The optimal configuration for a 100-node network has been identified at around 2000 to 2500 links, which achieves stability without excessive redundancy. These results are applied in the context of a private blockchain network that uses optimal connectivity to achieve high resilience and efficient resource allocation. The research findings suggest that adapting network configuration using greedy algorithms can contribute to the optimization of distributed systems, making them more stable and resilient to loads. |
| format | Article |
| id | doaj-art-fdd7661df5144aebbc1f0f47576fa8e6 |
| institution | Kabale University |
| issn | 2227-7080 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Technologies |
| spelling | doaj-art-fdd7661df5144aebbc1f0f47576fa8e62025-01-24T13:50:48ZengMDPI AGTechnologies2227-70802025-01-011313310.3390/technologies13010033Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain NetworksMiljenko Švarcmajer0Denis Ivanović1Tomislav Rudec2Ivica Lukić3Faculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, Kneza Trpimira 2b, 31000 Osijek, CroatiaFaculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, Kneza Trpimira 2b, 31000 Osijek, CroatiaFaculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, Kneza Trpimira 2b, 31000 Osijek, CroatiaFaculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, Kneza Trpimira 2b, 31000 Osijek, CroatiaThis paper investigates the application of graph theory and variants of greedy graph coloring algorithms for the optimization of distributed peer-to-peer networks, with a special focus on private blockchain networks. The graph coloring problem, as an NP-hard problem, presents a challenge in determining the minimum number of colors needed to efficiently allocate resources within the network. The paper deals with the influence of different graph density, i.e., the number of links, on the efficiency of greedy algorithms such as DSATUR, Descending, and Ascending. Experimental results show that increasing the number of links in the network contributes to a more uniform distribution of colors and increases the resistance of the network, whereby the DSATUR algorithm achieves the most uniform color saturation. The optimal configuration for a 100-node network has been identified at around 2000 to 2500 links, which achieves stability without excessive redundancy. These results are applied in the context of a private blockchain network that uses optimal connectivity to achieve high resilience and efficient resource allocation. The research findings suggest that adapting network configuration using greedy algorithms can contribute to the optimization of distributed systems, making them more stable and resilient to loads.https://www.mdpi.com/2227-7080/13/1/33greedy algorithmsgraph coloringDSATURdistributed systemspeer-to-peer networksconnectivity optimization |
| spellingShingle | Miljenko Švarcmajer Denis Ivanović Tomislav Rudec Ivica Lukić Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain Networks Technologies greedy algorithms graph coloring DSATUR distributed systems peer-to-peer networks connectivity optimization |
| title | Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain Networks |
| title_full | Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain Networks |
| title_fullStr | Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain Networks |
| title_full_unstemmed | Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain Networks |
| title_short | Application of Graph Theory and Variants of Greedy Graph Coloring Algorithms for Optimization of Distributed Peer-to-Peer Blockchain Networks |
| title_sort | application of graph theory and variants of greedy graph coloring algorithms for optimization of distributed peer to peer blockchain networks |
| topic | greedy algorithms graph coloring DSATUR distributed systems peer-to-peer networks connectivity optimization |
| url | https://www.mdpi.com/2227-7080/13/1/33 |
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