{"title":"基于mec的泛在时间约束分布式卸载模型","authors":"Shichao Guan, A. Boukerche","doi":"10.1109/DS-RT47707.2019.8958700","DOIUrl":null,"url":null,"abstract":"The advancements in mobile hardware and network technologies facilitate the processing power, storage capability, and connection quality. Such developments enable sophistic functions, ubiquitous power- and bandwidth-hungry applications that fundamentally changes the individual’s lifestyle. Although Cloud Computing technologies have already been leveraged to coordinate with the capability and battery-constraint mobile User Equipment (UE), the long-distance propagation delay downgrades the network QoS and user QoE. In this paper, we propose a queueing-based Mobile Edge Computing (MEC) model that concerns the offloading procedure, especially in the time-constraint scenarios. A queueing model is proposed for the offloading process, considering the dynamic network queueing delay. A heuristic scheduling model is designed to maximize the offloading energy and execution efficiency. A regression prediction model is implemented to achieve dynamic resource allocation. In the experiment, the proposed model is compared to the recent studies, and the results indicate that the proposed model can outperform the current studies in terms of execution time and energy reservation.","PeriodicalId":377914,"journal":{"name":"2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A MEC-based Distributed Offloading Model for Ubiquitous and Time-constraint Offloading\",\"authors\":\"Shichao Guan, A. Boukerche\",\"doi\":\"10.1109/DS-RT47707.2019.8958700\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The advancements in mobile hardware and network technologies facilitate the processing power, storage capability, and connection quality. Such developments enable sophistic functions, ubiquitous power- and bandwidth-hungry applications that fundamentally changes the individual’s lifestyle. Although Cloud Computing technologies have already been leveraged to coordinate with the capability and battery-constraint mobile User Equipment (UE), the long-distance propagation delay downgrades the network QoS and user QoE. In this paper, we propose a queueing-based Mobile Edge Computing (MEC) model that concerns the offloading procedure, especially in the time-constraint scenarios. A queueing model is proposed for the offloading process, considering the dynamic network queueing delay. A heuristic scheduling model is designed to maximize the offloading energy and execution efficiency. A regression prediction model is implemented to achieve dynamic resource allocation. In the experiment, the proposed model is compared to the recent studies, and the results indicate that the proposed model can outperform the current studies in terms of execution time and energy reservation.\",\"PeriodicalId\":377914,\"journal\":{\"name\":\"2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DS-RT47707.2019.8958700\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DS-RT47707.2019.8958700","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A MEC-based Distributed Offloading Model for Ubiquitous and Time-constraint Offloading
The advancements in mobile hardware and network technologies facilitate the processing power, storage capability, and connection quality. Such developments enable sophistic functions, ubiquitous power- and bandwidth-hungry applications that fundamentally changes the individual’s lifestyle. Although Cloud Computing technologies have already been leveraged to coordinate with the capability and battery-constraint mobile User Equipment (UE), the long-distance propagation delay downgrades the network QoS and user QoE. In this paper, we propose a queueing-based Mobile Edge Computing (MEC) model that concerns the offloading procedure, especially in the time-constraint scenarios. A queueing model is proposed for the offloading process, considering the dynamic network queueing delay. A heuristic scheduling model is designed to maximize the offloading energy and execution efficiency. A regression prediction model is implemented to achieve dynamic resource allocation. In the experiment, the proposed model is compared to the recent studies, and the results indicate that the proposed model can outperform the current studies in terms of execution time and energy reservation.