Reducing the Time of Live Container Migration in a Workflow

Di, Zhanyuan; Shao, En; He, Mujun

doi:10.1007/978-3-030-79478-1_23

Cited by 1 publication

(1 citation statement)

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“…Therefore, services in edge environments are being gradually provided in the form of containers. Moreover, real-time container migration is an important technology [7] that has triggered extensive research by technicians. Through real-time container migration, the containers in one device can be migrated to another device without user awareness.…”

Section: Introductionmentioning

confidence: 99%

Service Reliability Based on Fault Prediction and Container Migration in Edge Computing

Liu,

Kang,

et al. 2023

Applied Sciences

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With improvements in the computing capability of edge devices and the emergence of edge computing, an increasing number of services are being deployed on the edge side, and container-based virtualization is used to deploy services to improve resource utilization. This has led to challenges in reliability because services deployed on edge nodes are pruned owing to hardware failures and a lack of technical support. To solve this reliability problem, we propose a solution based on fault prediction combined with container migration to address the service failure problem caused by node failure. This approach comprises two major steps: fault prediction and container migration. Fault prediction collects the log of services on edge nodes and uses these data to conduct time-sequence modeling. Machine-learning algorithms are chosen to predict faults on the edge. Container migration is modeled as an optimization problem. A migration node selection approach based on a genetic algorithm is proposed to determine the most suitable migration target to migrate container services on the device and ensure the reliability of the services. Simulation results show that the proposed approach can effectively predict device faults and migrate services based on the optimal container migration strategy to avoid service failures deployed on edge devices and ensure service reliability.

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Section: Introductionmentioning

confidence: 99%