| CPC H04L 47/83 (2022.05) [G06F 9/50 (2013.01); H04L 47/76 (2013.01)] | 20 Claims |

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1. A resource allocation method for a cloud environment performed by one or more servers and comprising:
obtaining an initial resource requirement;
generating a first deployment parameter set according to the initial resource requirement by a first prediction model;
configuring the cloud environment according to the first deployment parameter set by a resource allocator;
obtaining and inputting a plurality of requests to a machine learning model in the cloud environment and generating a real resource requirement;
generating a predicted resource requirement at least according to the real resource requirement by a second prediction model;
in response to detecting that the cloud environment is in a busy state according to the predicted resource requirement by the resource allocator, generating a second deployment parameter set according to the real resource requirement by the first prediction model; and
reconfiguring the cloud environment according to the second deployment parameter set by the resource allocator.
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