Demo Abstract: Decomposing Data Analytics in Fog Networks

Ta Cheng Chang, Chege Gitau, Liang Zheng, Ching-Yao Huang, Maria Gorlatova, Mung Chiang

研究成果: Conference contribution同行評審

4 引文 斯高帕斯(Scopus)

摘要

Fog computing, the distribution of computing resources closer to the end devices along the cloud-to-things continuum, is recently emerging as an architecture for scaling of the Internet of Things (IoT) sensor networking applications. Fog computing requires novel computing program decompositions for heterogeneous hierarchical settings. To evaluate these new decompositions, we designed, developed, and instrumented a fog computing testbed that includes cloud computing and computing gateway execution points collaborating to finish complex data analytics operations. In this interactive demonstration we present one fog-specific algorithmic decomposition we recently examined and adapted for fog computing: a multi-execution point linear regression decomposition that jointly optimizes operation latency, quality, and costs. The demonstration highlights the role fog computing can play in future sensor networking architectures, and highlights some of the challenges of creating computing program decompositions for these architectures. An annotated video of the demonstration is available at [5].

原文English
主出版物標題SenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems
編輯Rasit Eskicioglu
發行者Association for Computing Machinery, Inc
ISBN(電子)9781450354592
DOIs
出版狀態Published - 6 11月 2017
事件15th ACM Conference on Embedded Networked Sensor Systems, SenSys 2017 - Delft, Netherlands
持續時間: 6 11月 20178 11月 2017

出版系列

名字SenSys 2017 - Proceedings of the 15th ACM Conference on Embedded Networked Sensor Systems
2017-January

Conference

Conference15th ACM Conference on Embedded Networked Sensor Systems, SenSys 2017
國家/地區Netherlands
城市Delft
期間6/11/178/11/17

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