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Data Analytics Service Composition and Deployment on Edge Devices

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Published:07 August 2018Publication History

ABSTRACT

Data analytics on edge devices has gained rapid growth in research, industry, and different aspects of our daily life. This topic still faces many challenges such as limited computation resource on edge devices. In this paper, we further identify two main challenges: the composition and deployment of data analytics services on edge devices. We present the Zoo system to address these two challenge: on one hand, it provides simple and concise domain-specific language to enable easy and and type-safe composition of different data analytics services; on the other, it utilises multiple deployment backends, including Docker container, JavaScript, and MirageOS, to accommodate the heterogeneous edge deployment environment. We show the expressiveness of Zoo with a use case, and thoroughly compare the performance of different deployment backends in evaluation.

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        • Published in

          cover image ACM Conferences
          Big-DAMA '18: Proceedings of the 2018 Workshop on Big Data Analytics and Machine Learning for Data Communication Networks
          August 2018
          58 pages
          ISBN:9781450359047
          DOI:10.1145/3229607

          Copyright © 2018 ACM

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          Publication History

          • Published: 7 August 2018

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