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My cloudy time machine: a scalable microservice-based platform for data processing in cloud-edge systems: a proof of concept for the ROBIN-cloud project

Published: 08 April 2019 Publication History

Abstract

As Cloud computing is a very well developed domain, many companies tend to move their entire activity in Cloud. At the same time, there is a tendency to move some of the data processing from Cloud to Edge as close as possible to the end devices. One main advantage of this approach is minimizing the latency in communication between the end devices and Cloud. Better usage of on premise devices is also a good achievement of the Edge offload. In this paper, we propose an architecture for applications that are connected to ROBIN-Cloud or to a general Cloud. We present how we have encapsulated Python-based microservices in Docker containers. We provide an implementation for the My Cloudy Time Machine application - GIGEL (Guided Intelligent GEared Legend), a nearby autonomous assistive robot. We use this prototype to evaluate the scalability of the proposed architecture. We also present results that show how to gain high performance by tuning a container-based embedded system.

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Cited By

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  • (2021)Storage service for edge computingProceedings of the 36th Annual ACM Symposium on Applied Computing10.1145/3412841.3441991(1165-1171)Online publication date: 22-Mar-2021
  • (2020)An Efficient Resource Scheduling Strategy for V2X Microservice Deployment in Edge ServersFuture Internet10.3390/fi1210017212:10(172)Online publication date: 15-Oct-2020
  • (2020)Near real-time scheduling in cloud-edge platformsProceedings of the 35th Annual ACM Symposium on Applied Computing10.1145/3341105.3374046(1264-1271)Online publication date: 30-Mar-2020
  • Show More Cited By

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  1. My cloudy time machine: a scalable microservice-based platform for data processing in cloud-edge systems: a proof of concept for the ROBIN-cloud project

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          cover image ACM Conferences
          SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing
          April 2019
          2682 pages
          ISBN:9781450359337
          DOI:10.1145/3297280
          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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          Published: 08 April 2019

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          Author Tags

          1. auto-scalability
          2. cloud computing
          3. data processing
          4. edge computing
          5. microservices

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          Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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          Cited By

          View all
          • (2021)Storage service for edge computingProceedings of the 36th Annual ACM Symposium on Applied Computing10.1145/3412841.3441991(1165-1171)Online publication date: 22-Mar-2021
          • (2020)An Efficient Resource Scheduling Strategy for V2X Microservice Deployment in Edge ServersFuture Internet10.3390/fi1210017212:10(172)Online publication date: 15-Oct-2020
          • (2020)Near real-time scheduling in cloud-edge platformsProceedings of the 35th Annual ACM Symposium on Applied Computing10.1145/3341105.3374046(1264-1271)Online publication date: 30-Mar-2020
          • (2020)Deadline-aware Scheduling in Cloud-Fog-Edge Systems2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)10.1109/CCGrid49817.2020.00-21(691-698)Online publication date: May-2020

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