Smart Containers Schedulers for Microservices Provision in Cloud-Fog-IoT Networks. Challenges and Opportunities
| Autor: | Rocío Pérez de Prado, Nicolás Ruiz-Reyes, José Enrique Muñoz-Expósito, Adam Marchewka, S. García-Galán |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
iot
Computer science Cloud computing Review 02 engineering and technology Microservices Computer security computer.software_genre lcsh:Chemical technology Biochemistry Analytical Chemistry Scheduling (computing) intelligent scheduling microservices 0202 electrical engineering electronic engineering information engineering lcsh:TP1-1185 Electrical and Electronic Engineering Instrumentation Implementation Soft computing soft-computing business.industry Quality of service cloud computing 020206 networking & telecommunications Energy consumption Cloud service provider Load balancing (computing) Atomic and Molecular Physics and Optics docker cloud service providers machine learning containers 020201 artificial intelligence & image processing fog computing business computer |
| Zdroj: | Sensors, Vol 20, Iss 6, p 1714 (2020) Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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