{"title":"无人机群充电:基于agent的仿真建模","authors":"Leonardo Grando, E. Ursini, Paulo S. Martins","doi":"10.1109/IEMCON51383.2020.9284939","DOIUrl":null,"url":null,"abstract":"This work seeks to address one of the most critical problems of Flying Ad Hoc Networks (FANET), which is the issue of recharging batteries coordination. For recharges to be carried out in the best possible way, the number of load devices (Base Stations) should not be excessively high so as not to burden the network. On the other hand, it is also necessary that when the drones want to recharge, there must always be a source of energy available. For this, we propose internal estimators that provide intelligence to the drones to try to predict the next charger attendance rate. The drones will not have communication with each other to recharge coordination but will continue to communicate concerning other routine activities (note that this communication is not considered in the scope of this model), that is, for recharging the batteries' coordination, there will be no energy expenditure on communication. The verification of the suitability of the proposal is done through Agent-Based Simulation and the use of three different policies for decision making. This will enable an approach that aims to optimize the operation of the system through a Nash equilibrium.","PeriodicalId":6871,"journal":{"name":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","volume":"13 1","pages":"0094-0100"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Drones Swarm Recharging: Modeling Using Agent-Based Simulation\",\"authors\":\"Leonardo Grando, E. Ursini, Paulo S. Martins\",\"doi\":\"10.1109/IEMCON51383.2020.9284939\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work seeks to address one of the most critical problems of Flying Ad Hoc Networks (FANET), which is the issue of recharging batteries coordination. For recharges to be carried out in the best possible way, the number of load devices (Base Stations) should not be excessively high so as not to burden the network. On the other hand, it is also necessary that when the drones want to recharge, there must always be a source of energy available. For this, we propose internal estimators that provide intelligence to the drones to try to predict the next charger attendance rate. The drones will not have communication with each other to recharge coordination but will continue to communicate concerning other routine activities (note that this communication is not considered in the scope of this model), that is, for recharging the batteries' coordination, there will be no energy expenditure on communication. The verification of the suitability of the proposal is done through Agent-Based Simulation and the use of three different policies for decision making. This will enable an approach that aims to optimize the operation of the system through a Nash equilibrium.\",\"PeriodicalId\":6871,\"journal\":{\"name\":\"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)\",\"volume\":\"13 1\",\"pages\":\"0094-0100\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMCON51383.2020.9284939\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMCON51383.2020.9284939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Drones Swarm Recharging: Modeling Using Agent-Based Simulation
This work seeks to address one of the most critical problems of Flying Ad Hoc Networks (FANET), which is the issue of recharging batteries coordination. For recharges to be carried out in the best possible way, the number of load devices (Base Stations) should not be excessively high so as not to burden the network. On the other hand, it is also necessary that when the drones want to recharge, there must always be a source of energy available. For this, we propose internal estimators that provide intelligence to the drones to try to predict the next charger attendance rate. The drones will not have communication with each other to recharge coordination but will continue to communicate concerning other routine activities (note that this communication is not considered in the scope of this model), that is, for recharging the batteries' coordination, there will be no energy expenditure on communication. The verification of the suitability of the proposal is done through Agent-Based Simulation and the use of three different policies for decision making. This will enable an approach that aims to optimize the operation of the system through a Nash equilibrium.