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Benefiting from the convenience of virtualization, virtual machine migration is generally utilized to fulfil optimization objectives in cloud/edge computing. However, live migration has certain risks and unapt decision may lead to side effects and performance degradation. Leveraging modified deep Q network, this paper provided an advanced risk evaluation system. Thorough formulation was given in this paper and a specific integration method was innovated based on uncertain theory. Series experiments were carried on computing cluster with OpenStack. The experimental results showed deep Q network for risk system was reliable while the uncertain approach was a proper way to deal with the risk integration.

A Specific Risk Evaluation System for Live Virtual Machine Migration Based on the Uncertain Theory