Literature DB >> 32204390

Smart Containers Schedulers for Microservices Provision in Cloud-Fog-IoT Networks. Challenges and Opportunities.

Rocío Pérez de Prado1, Sebastián García-Galán1, José Enrique Muñoz-Expósito1, Adam Marchewka2, Nicolás Ruiz-Reyes1.   

Abstract

Docker containers are the lightweight-virtualization technology prevailing today for the provision of microservices. This work raises and discusses two main challenges in Docker containers' scheduling in cloud-fog-internet of things (IoT) networks. First, the convenience to integrate intelligent containers' schedulers based on soft-computing in the dominant open-source containers' management platforms: Docker Swarm, Google Kubernetes and Apache Mesos. Secondly, the need for specific intelligent containers' schedulers for the different interfaces in cloud-fog-IoT networks: cloud-to-fog, fog-to-IoT and cloud-to-fog. The goal of this work is to support the optimal allocation of microservices provided by the main cloud service providers today and used by millions of users worldwide in applications such as smart health, content delivery networks, smart health, etc. Particularly, the improvement is studied in terms of quality of service (QoS) parameters such as latency, load balance, energy consumption and runtime, based on the analysis of previous works and implementations. Moreover, the scientific-technical impact of smart containers' scheduling in the market is also discussed, showing the possible repercussion of the raised opportunities in the research line.

Entities:  

Keywords:  IoT; cloud computing; cloud service providers; containers; docker; fog computing; intelligent scheduling; machine learning; microservices; soft-computing

Year:  2020        PMID: 32204390     DOI: 10.3390/s20061714

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Containerized Architecture Performance Analysis for IoT Framework Based on Enhanced Fire Prevention Case Study: Rwanda.

Authors:  Eric Hitimana; Gaurav Bajpai; Richard Musabe; Louis Sibomana; Kayavizhi Jayavel
Journal:  Sensors (Basel)       Date:  2022-08-27       Impact factor: 3.847

  1 in total

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