DNN task offloading method and terminal in an edge-cloud hybrid computing environment
A hybrid computing and task technology, applied in computing, energy-saving computing, neural learning methods, etc., can solve problems such as long response time, reduce delay, network congestion, etc., achieve accurate cost estimation, ensure feasibility, and reduce costs. Effect
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Embodiment 1
[0108] First construct the DNN task offloading system model under the edge-cloud hybrid environment,
[0110] M={m
[0111]
[0112] S={s
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[0116] t
[0117] Wherein, the types of computing nodes include: mobile device nodes, edge nodes and cloud nodes;
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[0122] Each DNN task to be unloaded is executed on a computing node, and a DNN task can only be
[0124] Complete the unloading of the DNN task within the specified time, i.e. t
[0126] S3, construct an initialization population according to the solution set, each solution in the solution set corresponds to the initialization population
[0127] Wherein, the subtasks that are scheduled to the same computing node are executed first if they arrive first;
Embodiment 2
[0135] The pBset
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Embodiment 3
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