Mohamed El Ghmary, Youssef Hmimz, T. Chanyour, Ali Ouacha, Mohammed Ouçamah Cherkaoui Malki
{"title":"移动边缘计算环境下的多任务卸载与计算资源管理","authors":"Mohamed El Ghmary, Youssef Hmimz, T. Chanyour, Ali Ouacha, Mohammed Ouçamah Cherkaoui Malki","doi":"10.1109/CloudTech49835.2020.9365903","DOIUrl":null,"url":null,"abstract":"In Mobile Cloud Computing, Smart Mobile Devices (SMDs) and Cloud Computing are combined to create a new infrastructure that allows data processing and storage outside the device. The Internet of Things refers to the billions of physical devices that are connected to the Internet. With the rapid development of these, it is clear that the requirements are largely based on the need for autonomous devices to facilitate the services required by applications that require rapid response time and flexible mobility. In this article, we study the management of computational resources and the trade-off between the consumed energy by an SMD and the processing time of its tasks. For this, we define a system model, a problem formulation and offer heuristic solutions for offloading tasks in order to jointly optimize the allocation of computing resources under limited energy and sensitive latency. In addition, we use the residual energy of the SMD battery and the sensitive latency of its tasks in defining the weighting factor of energy consumption and processing time.","PeriodicalId":272860,"journal":{"name":"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Multi-task Offloading and Computational Resources Management in a Mobile Edge Computing Environment\",\"authors\":\"Mohamed El Ghmary, Youssef Hmimz, T. Chanyour, Ali Ouacha, Mohammed Ouçamah Cherkaoui Malki\",\"doi\":\"10.1109/CloudTech49835.2020.9365903\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Mobile Cloud Computing, Smart Mobile Devices (SMDs) and Cloud Computing are combined to create a new infrastructure that allows data processing and storage outside the device. The Internet of Things refers to the billions of physical devices that are connected to the Internet. With the rapid development of these, it is clear that the requirements are largely based on the need for autonomous devices to facilitate the services required by applications that require rapid response time and flexible mobility. In this article, we study the management of computational resources and the trade-off between the consumed energy by an SMD and the processing time of its tasks. For this, we define a system model, a problem formulation and offer heuristic solutions for offloading tasks in order to jointly optimize the allocation of computing resources under limited energy and sensitive latency. In addition, we use the residual energy of the SMD battery and the sensitive latency of its tasks in defining the weighting factor of energy consumption and processing time.\",\"PeriodicalId\":272860,\"journal\":{\"name\":\"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CloudTech49835.2020.9365903\",\"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 5th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudTech49835.2020.9365903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-task Offloading and Computational Resources Management in a Mobile Edge Computing Environment
In Mobile Cloud Computing, Smart Mobile Devices (SMDs) and Cloud Computing are combined to create a new infrastructure that allows data processing and storage outside the device. The Internet of Things refers to the billions of physical devices that are connected to the Internet. With the rapid development of these, it is clear that the requirements are largely based on the need for autonomous devices to facilitate the services required by applications that require rapid response time and flexible mobility. In this article, we study the management of computational resources and the trade-off between the consumed energy by an SMD and the processing time of its tasks. For this, we define a system model, a problem formulation and offer heuristic solutions for offloading tasks in order to jointly optimize the allocation of computing resources under limited energy and sensitive latency. In addition, we use the residual energy of the SMD battery and the sensitive latency of its tasks in defining the weighting factor of energy consumption and processing time.