A cloud task scheduling method
A task scheduling and task technology, applied in the field of cloud computing, can solve the problem of not considering the optimization goal of the resource side, not considering the problem of resource energy consumption, hidden dangers of service efficiency, etc., and achieve the effect of balanced optimal task scheduling
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[0020] as figure 1 The directed acyclic graph DAG shown represents the executed task model, and the task model is denoted as G t =(V,E), where V represents the set of tasks, V={v 1 ,v 2 ,...,v n}, v i ∈V, E represents the set of directed edges between tasks, edge e i,j =(v i ,v j ) ∈ E represents the task v i with v j The directed edge between, if e i,j =1, it means that in G t Medium task v i The output of task v j input; if e i,j = 0, it means task v i with v j no direct connection between vc i Indicates the task v i The number of CPU calculation cycles required, d i,j Indicates the task v i with v j The amount of data transferred between them (unit: KB).
[0021] by figure 2 The directed graph shown represents the cloud resource model, and the cloud resource model is denoted as G r =(R,L), where G represents the collection of cloud resources, R={r 1 ,r 2 ,...,r m}, r i ∈R, L represents the communication link between resources, l h,k =(r h ,r k ...
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