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Long-tailed distributions in grid complex network
| Content Provider | ACM Digital Library |
|---|---|
| Author | IlijaĊĦic, Lovro Saitta, Lorenza |
| Abstract | A large-scale analysis of the grid log data is here performed in order to recognize relations that may appear on the global level and are not observable when exploring any specific part of the grid. Grid, including its users, is modeled as a Complex Network in order to use analysis methods available from Complex Network Science. When investigating node degrees, strengths and job length parameters, the results demonstrate certain behaviors and distributions that are present in many natural phenomena, giving thus the representation of Grid as a complex system. |
| Starting Page | 21 |
| Ending Page | 30 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450301008 |
| DOI | 10.1145/1809029.1809032 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-06-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Complex networks Grid computing Job length distributions Generative models Degree distributions |
| Content Type | Text |
| Resource Type | Article |
