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

Area of Science:

• Computer Science
• Cloud Computing
• Internet of Things (IoT)

Background:

• Docker containers are a prevalent lightweight virtualization technology for microservices.
• Cloud-fog-IoT networks present unique challenges for container scheduling.
• Existing management platforms like Docker Swarm, Kubernetes, and Mesos require integration of intelligent schedulers.

Purpose of the Study:

• To discuss challenges in integrating soft-computing-based intelligent schedulers into dominant container management platforms.
• To highlight the need for specific intelligent schedulers tailored to cloud-fog-IoT network interfaces (cloud-to-fog, fog-to-IoT).
• To support optimal microservice allocation for improved Quality of Service (QoS) in cloud-fog-IoT environments.

Main Methods:

• Analysis of existing works and implementations related to Docker container scheduling.
• Discussion of integration strategies for intelligent schedulers in cloud-fog-IoT networks.
• Evaluation of potential improvements in QoS parameters like latency, load balance, energy consumption, and runtime.

Main Results:

• Identified challenges in integrating intelligent schedulers into mainstream platforms.
• Emphasized the necessity of specialized schedulers for different cloud-fog-IoT interfaces.
• Demonstrated potential QoS improvements through intelligent container scheduling.

Conclusions:

• Intelligent Docker container scheduling is crucial for optimizing microservices in cloud-fog-IoT networks.
• Tailored schedulers can significantly enhance QoS parameters, impacting applications like smart health and CDNs.
• This research opens avenues for further investigation into smart container scheduling's market impact.