{"title":"基于改进遗传算法的综合测试平台测试任务管理调度研究","authors":"Dandan Guo, Luohui Xia, Yongjun Wang, Lili Liang, Cuiya Qin, Tongle Fan","doi":"10.1109/ACCC58361.2022.00011","DOIUrl":null,"url":null,"abstract":"As the application range of iot terminal becomes wider and wider, people put forward higher requirements on the performance of iot device, which leads to a huge increase in the testing tasks of iot terminal device. In order to solve the problems of complex system structure, resource waste and low detection efficiency of the current detection equipment, this paper proposes a test task scheduling strategy based on improved genetic algorithm. By updating fitness function, the test task order is optimized and the test resources of the integrated test platform are rationally utilized. Based on the simulation results, the improved algorithm proposed in this paper can effectively improve the task test efficiency and maximize the test benefits.","PeriodicalId":285531,"journal":{"name":"2022 3rd Asia Conference on Computers and Communications (ACCC)","volume":"15 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Test Task Management Scheduling of Integrated Test Platform Based on Improved Genetic Algorithm\",\"authors\":\"Dandan Guo, Luohui Xia, Yongjun Wang, Lili Liang, Cuiya Qin, Tongle Fan\",\"doi\":\"10.1109/ACCC58361.2022.00011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the application range of iot terminal becomes wider and wider, people put forward higher requirements on the performance of iot device, which leads to a huge increase in the testing tasks of iot terminal device. In order to solve the problems of complex system structure, resource waste and low detection efficiency of the current detection equipment, this paper proposes a test task scheduling strategy based on improved genetic algorithm. By updating fitness function, the test task order is optimized and the test resources of the integrated test platform are rationally utilized. Based on the simulation results, the improved algorithm proposed in this paper can effectively improve the task test efficiency and maximize the test benefits.\",\"PeriodicalId\":285531,\"journal\":{\"name\":\"2022 3rd Asia Conference on Computers and Communications (ACCC)\",\"volume\":\"15 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd Asia Conference on Computers and Communications (ACCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACCC58361.2022.00011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd Asia Conference on Computers and Communications (ACCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACCC58361.2022.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Test Task Management Scheduling of Integrated Test Platform Based on Improved Genetic Algorithm
As the application range of iot terminal becomes wider and wider, people put forward higher requirements on the performance of iot device, which leads to a huge increase in the testing tasks of iot terminal device. In order to solve the problems of complex system structure, resource waste and low detection efficiency of the current detection equipment, this paper proposes a test task scheduling strategy based on improved genetic algorithm. By updating fitness function, the test task order is optimized and the test resources of the integrated test platform are rationally utilized. Based on the simulation results, the improved algorithm proposed in this paper can effectively improve the task test efficiency and maximize the test benefits.