{"title":"基于体积,大小,切割和时间的图划分VSCT算法","authors":"Chayma Sakouhi, Abir Khaldi, H. Ghézala","doi":"10.1080/17445760.2023.2174540","DOIUrl":null,"url":null,"abstract":"Dealing with large-scale graphs requires an efficient graph partitioner that produces balanced partitions with fewer cut edges/vertices in a reasonable amount of time. Despite several algorithms that have been proposed, it is still insufficient. Even with the continuous growth of graph volume, they do not consider the graph volume during graph partitioning. Therefore, these algorithms generate an imbalanced workload. We propose a graph partitioner algorithm VSCT based essentially on four key metrics: Volume, Size, Cuts, and Time to maintain high-quality graph partitioning. Using real-world datasets, we show that VSCT performs an efficient partitioning quality against the existing graph partitioning algorithms.","PeriodicalId":45411,"journal":{"name":"International Journal of Parallel Emergent and Distributed Systems","volume":"38 1","pages":"181 - 197"},"PeriodicalIF":0.6000,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"VSCT algorithm for graph partitioning based on volume, size, cuts and time\",\"authors\":\"Chayma Sakouhi, Abir Khaldi, H. Ghézala\",\"doi\":\"10.1080/17445760.2023.2174540\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dealing with large-scale graphs requires an efficient graph partitioner that produces balanced partitions with fewer cut edges/vertices in a reasonable amount of time. Despite several algorithms that have been proposed, it is still insufficient. Even with the continuous growth of graph volume, they do not consider the graph volume during graph partitioning. Therefore, these algorithms generate an imbalanced workload. We propose a graph partitioner algorithm VSCT based essentially on four key metrics: Volume, Size, Cuts, and Time to maintain high-quality graph partitioning. Using real-world datasets, we show that VSCT performs an efficient partitioning quality against the existing graph partitioning algorithms.\",\"PeriodicalId\":45411,\"journal\":{\"name\":\"International Journal of Parallel Emergent and Distributed Systems\",\"volume\":\"38 1\",\"pages\":\"181 - 197\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Parallel Emergent and Distributed Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/17445760.2023.2174540\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Parallel Emergent and Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17445760.2023.2174540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
VSCT algorithm for graph partitioning based on volume, size, cuts and time
Dealing with large-scale graphs requires an efficient graph partitioner that produces balanced partitions with fewer cut edges/vertices in a reasonable amount of time. Despite several algorithms that have been proposed, it is still insufficient. Even with the continuous growth of graph volume, they do not consider the graph volume during graph partitioning. Therefore, these algorithms generate an imbalanced workload. We propose a graph partitioner algorithm VSCT based essentially on four key metrics: Volume, Size, Cuts, and Time to maintain high-quality graph partitioning. Using real-world datasets, we show that VSCT performs an efficient partitioning quality against the existing graph partitioning algorithms.