{"title":"Cooperative Fog Communications using A Multi-Level Load Balancing","authors":"Nour Mostafa","doi":"10.1109/FMEC.2019.8795325","DOIUrl":null,"url":null,"abstract":"Fog Computing has been introduced as an emergence technology in Internet of Things (IoT). Fog Computing is introduced as a solution for many enterprises, which include computation, storage, and data exchange capabilities of edge, devises. Users, resources, and data are steadily increasing in number, making scalability and extensibility important issues. With the emergence of the Cloud/Fog it is expected that run time estimates will also be used for resource selection, workflow management, load balancing, and job monitoring. User preferences is the core elements of the fog/cloud service provider, as the idea is to learn, predict, optimize etc. Predictions are a very important step towards automatic resource management. This paper proposes a cooperative fogs system, which consider the user preferences e.g. delay, cost, and privacy and find the optimal choice that meet the user preferences. In addition to ensuring efficient utilization of resources to balance the load in fog computing.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FMEC.2019.8795325","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Fog Computing has been introduced as an emergence technology in Internet of Things (IoT). Fog Computing is introduced as a solution for many enterprises, which include computation, storage, and data exchange capabilities of edge, devises. Users, resources, and data are steadily increasing in number, making scalability and extensibility important issues. With the emergence of the Cloud/Fog it is expected that run time estimates will also be used for resource selection, workflow management, load balancing, and job monitoring. User preferences is the core elements of the fog/cloud service provider, as the idea is to learn, predict, optimize etc. Predictions are a very important step towards automatic resource management. This paper proposes a cooperative fogs system, which consider the user preferences e.g. delay, cost, and privacy and find the optimal choice that meet the user preferences. In addition to ensuring efficient utilization of resources to balance the load in fog computing.