Mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithm
In order to improve the effectiveness of mobile network scheduling operation information, a method of mobile network scheduling operation information sharing based on chaos reverse learning improved gray wolf algorithm was proposed.On the basis of studying the information sharing structure between t...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2023-08-01
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| Series: | Dianxin kexue |
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| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023164/ |
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| _version_ | 1841530832787865600 |
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| author | Xinyue YU Yipu ZHANG Yong ZHANG Lin YANG Weidong GAO Yan GUO |
| author_facet | Xinyue YU Yipu ZHANG Yong ZHANG Lin YANG Weidong GAO Yan GUO |
| author_sort | Xinyue YU |
| collection | DOAJ |
| description | In order to improve the effectiveness of mobile network scheduling operation information, a method of mobile network scheduling operation information sharing based on chaos reverse learning improved gray wolf algorithm was proposed.On the basis of studying the information sharing structure between the information intranet/provincial dispatching demilitarized zone (DMZ) and the network/provincial dispatching III area, the information sharing was realized through a three-layer scheduling network model including the sharing task layer, the information layer and the user layer, and the information scheduling optimization objective function to maximize the information utility was determined, and the information scheduling results were obtained by solving the objective function through the grey wolf algorithm.In order to obtain better solution results of the objective function, chaos reverse learning and information sharing search strategy were introduced to optimize the initial population and communication ability of the grey wolf algorithm, so as to obtain better solution results and realize the optimal information sharing.The test results show that the method has good application performance.The information utility values are all above 20, the deviation rate is lower than 0.12, and the goodness of fit is higher than 0.92.It can complete information sharing under different transmission modes and present the details of shared information. |
| format | Article |
| id | doaj-art-7126734b49c94f77b61da3a881d87d7e |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2023-08-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-7126734b49c94f77b61da3a881d87d7e2025-01-15T02:58:18ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012023-08-0139829059562758Mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithmXinyue YUYipu ZHANGYong ZHANGLin YANGWeidong GAOYan GUOIn order to improve the effectiveness of mobile network scheduling operation information, a method of mobile network scheduling operation information sharing based on chaos reverse learning improved gray wolf algorithm was proposed.On the basis of studying the information sharing structure between the information intranet/provincial dispatching demilitarized zone (DMZ) and the network/provincial dispatching III area, the information sharing was realized through a three-layer scheduling network model including the sharing task layer, the information layer and the user layer, and the information scheduling optimization objective function to maximize the information utility was determined, and the information scheduling results were obtained by solving the objective function through the grey wolf algorithm.In order to obtain better solution results of the objective function, chaos reverse learning and information sharing search strategy were introduced to optimize the initial population and communication ability of the grey wolf algorithm, so as to obtain better solution results and realize the optimal information sharing.The test results show that the method has good application performance.The information utility values are all above 20, the deviation rate is lower than 0.12, and the goodness of fit is higher than 0.92.It can complete information sharing under different transmission modes and present the details of shared information.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023164/chaos reverse learningimproved grey wolf algorithmmobile networkdispatch operationinformation sharingsharing search policy |
| spellingShingle | Xinyue YU Yipu ZHANG Yong ZHANG Lin YANG Weidong GAO Yan GUO Mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithm Dianxin kexue chaos reverse learning improved grey wolf algorithm mobile network dispatch operation information sharing sharing search policy |
| title | Mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithm |
| title_full | Mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithm |
| title_fullStr | Mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithm |
| title_full_unstemmed | Mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithm |
| title_short | Mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithm |
| title_sort | mobile network scheduling and operation information sharing method based on chaos reverse learning improved grey wolf algorithm |
| topic | chaos reverse learning improved grey wolf algorithm mobile network dispatch operation information sharing sharing search policy |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023164/ |
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