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Performance Evaluation of Container Orchestration Tools in Edge Computing Environments.
Ivan Čilić1, Petar Krivić1, Ivana Podnar Žarko1
1Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.
Sensors (Basel, Switzerland)
|April 28, 2023
Summary
Edge computing enhances service delivery by moving resources closer to users. Kubernetes shows promise for edge orchestration, but challenges remain for dynamic, distributed environments.
Area of Science:
- Computer Science
- Distributed Systems
- Cloud Computing
Background:
- Edge computing offers improved service delivery and performance by extending cloud resources closer to the service environment.
- Existing research often relies on simulations within closed networks, limiting real-world applicability.
- Analysis of current edge computing implementations and their orchestration platforms is needed.
Purpose of the Study:
- To analyze existing edge computing processing environments, focusing on Quality of Service (QoS) parameters and orchestration platforms.
- To evaluate popular edge orchestration platforms for their ability to integrate remote devices and adapt scheduling algorithms.
- To assess the readiness of these platforms for real-world edge computing deployments.
Main Methods:
- Comparative analysis of existing edge resource processing environments.
- Evaluation of edge orchestration platforms based on workflow for remote device inclusion and scheduling algorithm adaptability.
- Experimental performance comparison of selected platforms in realistic network and execution settings.
Main Results:
- Kubernetes and its distributions demonstrate potential for effective edge resource scheduling.
- The study identifies current limitations in adapting edge orchestration tools for dynamic and distributed environments.
- Performance comparisons highlight the readiness status of platforms for edge computing.
Conclusions:
- Kubernetes-based solutions show significant promise for edge computing orchestration.
- Further development is required to fully adapt current tools for the complexities of dynamic and distributed edge environments.
- The findings provide insights into the practical application and challenges of edge computing implementations.
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