{"title":"一种基于改进NSGA-II的无线自组网任务调度算法","authors":"Liang Dai, Hongke Xu, Ting Chen, Xue Li","doi":"10.1109/ICSPCC.2013.6664096","DOIUrl":null,"url":null,"abstract":"To solve the problem the lower efficiency of task-performing caused by the mobility and failure-prone of ad hoc nodes, a multi-object optimization task scheduling algorithm (MOTA) is proposed for wireless ad hoc networks. This algorithm tries its best to make less Makespan, but meanwhile, it also pay much more attention to the failure probability and the energy-consuming of nodes. MOTA avoids the task assigned to the failure-prone node, which effectively reducing the effect of failed nodes on task-performing. Simulation results show that the proposed algorithm can trade off these three objectives well. Compared with the traditional task scheduling algorithms, simulation experiments obtain better results.","PeriodicalId":124509,"journal":{"name":"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A task scheduling algorithm based on improved NSGA-II for wireless ad hoc networks\",\"authors\":\"Liang Dai, Hongke Xu, Ting Chen, Xue Li\",\"doi\":\"10.1109/ICSPCC.2013.6664096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problem the lower efficiency of task-performing caused by the mobility and failure-prone of ad hoc nodes, a multi-object optimization task scheduling algorithm (MOTA) is proposed for wireless ad hoc networks. This algorithm tries its best to make less Makespan, but meanwhile, it also pay much more attention to the failure probability and the energy-consuming of nodes. MOTA avoids the task assigned to the failure-prone node, which effectively reducing the effect of failed nodes on task-performing. Simulation results show that the proposed algorithm can trade off these three objectives well. Compared with the traditional task scheduling algorithms, simulation experiments obtain better results.\",\"PeriodicalId\":124509,\"journal\":{\"name\":\"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPCC.2013.6664096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Signal Processing, Communication and Computing (ICSPCC 2013)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCC.2013.6664096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A task scheduling algorithm based on improved NSGA-II for wireless ad hoc networks
To solve the problem the lower efficiency of task-performing caused by the mobility and failure-prone of ad hoc nodes, a multi-object optimization task scheduling algorithm (MOTA) is proposed for wireless ad hoc networks. This algorithm tries its best to make less Makespan, but meanwhile, it also pay much more attention to the failure probability and the energy-consuming of nodes. MOTA avoids the task assigned to the failure-prone node, which effectively reducing the effect of failed nodes on task-performing. Simulation results show that the proposed algorithm can trade off these three objectives well. Compared with the traditional task scheduling algorithms, simulation experiments obtain better results.