Jun Liu, Yuwei Zhang, Jing Wang, Tao Cui, Lin Zhang, C. Li, Kai Chen, Sun Li, Sunli Feng, Dongqing Xie, Dahua Fan, Jianghong Ou, Yun Li, Haige Xiang, Kaimeno Dube, Abbarbas Muazu, Nakilavai Rono, Fusheng Zhu, Liming Chen, Wenvong Zhou, Zhusong Liu
{"title":"无人机辅助移动边缘计算网络的中断概率分析","authors":"Jun Liu, Yuwei Zhang, Jing Wang, Tao Cui, Lin Zhang, C. Li, Kai Chen, Sun Li, Sunli Feng, Dongqing Xie, Dahua Fan, Jianghong Ou, Yun Li, Haige Xiang, Kaimeno Dube, Abbarbas Muazu, Nakilavai Rono, Fusheng Zhu, Liming Chen, Wenvong Zhou, Zhusong Liu","doi":"10.4108/eetinis.v9i31.960","DOIUrl":null,"url":null,"abstract":"This paper studies one typical mobile edge computing (MEC) system, where a single user has some intensively calculating tasks to be computed by M edge nodes (ENs) with much more powerful calculating capability. In particular, unmanned aerial vehicle (UAV) can act as the ENs due to its flexibility and high mobility in the deployment. For this system, we propose several EN selection criteria to improve the system whole performance of computation and communication. Specifically, criterion I selects the best EN based on maximizing the received signal-to-noise ratio (SNR) at the EN, criterion II performs the selection according to the most powerful calculating capability, while criterion III chooses one EN randomly. For each EN selection criterion, we perform the system performance evaluation by analyzing outage probability (OP) through deriving some analytical expressions. From these expressions, we can obtain some meaningful insights regarding how to design the MEC system. We finally perform some simulation results to demonstrate the effectiveness of the proposed MEC network. In particular, criterion I can exploit the full diversity order equal to M.","PeriodicalId":33474,"journal":{"name":"EAI Endorsed Transactions on Industrial Networks and Intelligent Systems","volume":"2016 1","pages":"4"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Outage Probability Analysis for UAV-Aided Mobile Edge Computing Networks\",\"authors\":\"Jun Liu, Yuwei Zhang, Jing Wang, Tao Cui, Lin Zhang, C. Li, Kai Chen, Sun Li, Sunli Feng, Dongqing Xie, Dahua Fan, Jianghong Ou, Yun Li, Haige Xiang, Kaimeno Dube, Abbarbas Muazu, Nakilavai Rono, Fusheng Zhu, Liming Chen, Wenvong Zhou, Zhusong Liu\",\"doi\":\"10.4108/eetinis.v9i31.960\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies one typical mobile edge computing (MEC) system, where a single user has some intensively calculating tasks to be computed by M edge nodes (ENs) with much more powerful calculating capability. In particular, unmanned aerial vehicle (UAV) can act as the ENs due to its flexibility and high mobility in the deployment. For this system, we propose several EN selection criteria to improve the system whole performance of computation and communication. Specifically, criterion I selects the best EN based on maximizing the received signal-to-noise ratio (SNR) at the EN, criterion II performs the selection according to the most powerful calculating capability, while criterion III chooses one EN randomly. For each EN selection criterion, we perform the system performance evaluation by analyzing outage probability (OP) through deriving some analytical expressions. From these expressions, we can obtain some meaningful insights regarding how to design the MEC system. We finally perform some simulation results to demonstrate the effectiveness of the proposed MEC network. In particular, criterion I can exploit the full diversity order equal to M.\",\"PeriodicalId\":33474,\"journal\":{\"name\":\"EAI Endorsed Transactions on Industrial Networks and Intelligent Systems\",\"volume\":\"2016 1\",\"pages\":\"4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EAI Endorsed Transactions on Industrial Networks and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4108/eetinis.v9i31.960\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EAI Endorsed Transactions on Industrial Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/eetinis.v9i31.960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
Outage Probability Analysis for UAV-Aided Mobile Edge Computing Networks
This paper studies one typical mobile edge computing (MEC) system, where a single user has some intensively calculating tasks to be computed by M edge nodes (ENs) with much more powerful calculating capability. In particular, unmanned aerial vehicle (UAV) can act as the ENs due to its flexibility and high mobility in the deployment. For this system, we propose several EN selection criteria to improve the system whole performance of computation and communication. Specifically, criterion I selects the best EN based on maximizing the received signal-to-noise ratio (SNR) at the EN, criterion II performs the selection according to the most powerful calculating capability, while criterion III chooses one EN randomly. For each EN selection criterion, we perform the system performance evaluation by analyzing outage probability (OP) through deriving some analytical expressions. From these expressions, we can obtain some meaningful insights regarding how to design the MEC system. We finally perform some simulation results to demonstrate the effectiveness of the proposed MEC network. In particular, criterion I can exploit the full diversity order equal to M.