{"title":"Edge-Stream: a Stream Processing Approach for Distributed Applications on a Hierarchical Edge-computing System","authors":"Xiaoyang Wang, Zhe Zhou, Ping Han, Tong Meng, Guangyu Sun, Jidong Zhai","doi":"10.1109/SEC50012.2020.00009","DOIUrl":null,"url":null,"abstract":"With the rapid growth of IoT devices, the traditional cloud computing scheme is inefficient for many IoT based applications, mainly due to network data flood, long latency, and privacy issues. To this end, the edge computing scheme is proposed to mitigate these problems. However, in an edge computing system, the application development becomes more complicated as it involves increasing levels of edge nodes. Although some efforts have been introduced, existing edge computing frameworks still have some limitations in various application scenarios. To overcome these limitations, we propose a new programming model called Edge-Stream. It is a simple and programmer-friendly model, which can cover typical scenarios in edge-computing. Besides, we address several new issues, such as data sharing and area awareness, in this model. We also implement a prototype of edge-computing framework based on the Edge-Stream model. A comprehensive evaluation is provided based on the prototype. Experimental results demonstrate the effectiveness of the model.","PeriodicalId":375577,"journal":{"name":"2020 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE/ACM Symposium on Edge Computing (SEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEC50012.2020.00009","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
With the rapid growth of IoT devices, the traditional cloud computing scheme is inefficient for many IoT based applications, mainly due to network data flood, long latency, and privacy issues. To this end, the edge computing scheme is proposed to mitigate these problems. However, in an edge computing system, the application development becomes more complicated as it involves increasing levels of edge nodes. Although some efforts have been introduced, existing edge computing frameworks still have some limitations in various application scenarios. To overcome these limitations, we propose a new programming model called Edge-Stream. It is a simple and programmer-friendly model, which can cover typical scenarios in edge-computing. Besides, we address several new issues, such as data sharing and area awareness, in this model. We also implement a prototype of edge-computing framework based on the Edge-Stream model. A comprehensive evaluation is provided based on the prototype. Experimental results demonstrate the effectiveness of the model.