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Review

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

by
Rocío Pérez de Prado
1,*,
Sebastián García-Galán
1,
José Enrique Muñoz-Expósito
1,
Adam Marchewka
2 and
Nicolás Ruiz-Reyes
1
1
Telecommunication Engineering Department, University of Jaén, Science and Technology Campus, 23700 Linares (Jaén), Spain
2
Institute of Telecommunications and Informatics, University of Technology and Life Sciences, Prof. S. Kaliskiego 7, 85-791 Bydgoszcz, Poland
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(6), 1714; https://doi.org/10.3390/s20061714
Submission received: 24 February 2020 / Revised: 15 March 2020 / Accepted: 17 March 2020 / Published: 19 March 2020
(This article belongs to the Special Issue Advanced Management of Fog/Edge Networks and IoT Sensors Devices)
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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.
Keywords: fog computing; IoT; cloud computing; soft-computing; machine learning; containers; docker; microservices; intelligent scheduling; cloud service providers fog computing; IoT; cloud computing; soft-computing; machine learning; containers; docker; microservices; intelligent scheduling; cloud service providers

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MDPI and ACS Style

Pérez de Prado, R.; García-Galán, S.; Muñoz-Expósito, J.E.; Marchewka, A.; Ruiz-Reyes, N. Smart Containers Schedulers for Microservices Provision in Cloud-Fog-IoT Networks. Challenges and Opportunities. Sensors 2020, 20, 1714. https://doi.org/10.3390/s20061714

AMA Style

Pérez de Prado R, García-Galán S, Muñoz-Expósito JE, Marchewka A, Ruiz-Reyes N. Smart Containers Schedulers for Microservices Provision in Cloud-Fog-IoT Networks. Challenges and Opportunities. Sensors. 2020; 20(6):1714. https://doi.org/10.3390/s20061714

Chicago/Turabian Style

Pérez de Prado, Rocío, Sebastián García-Galán, José Enrique Muñoz-Expósito, Adam Marchewka, and Nicolás Ruiz-Reyes. 2020. "Smart Containers Schedulers for Microservices Provision in Cloud-Fog-IoT Networks. Challenges and Opportunities" Sensors 20, no. 6: 1714. https://doi.org/10.3390/s20061714

APA Style

Pérez de Prado, R., García-Galán, S., Muñoz-Expósito, J. E., Marchewka, A., & Ruiz-Reyes, N. (2020). Smart Containers Schedulers for Microservices Provision in Cloud-Fog-IoT Networks. Challenges and Opportunities. Sensors, 20(6), 1714. https://doi.org/10.3390/s20061714

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