Cloud workflow task clustering method supporting dependency and time balance
A clustering method and workflow technology, applied in the direction of program startup/switching, program control design, instruments, etc., can solve the problem of delaying the start time of the next level task, and achieve the effect of reducing the completion time and clustering scientifically and reasonably
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[0031] The cloud workflow scheduling method supporting dependency balance clustering provided by the present invention will be described in detail below.
[0032] For the convenience of description, the relevant symbols are defined as follows:
[0033] taskList: The set of tasks contained in a certain level in the flowchart.
[0034] clusterNum: the number of clusters.
[0035] W=(T,E): workflow, where T={t 1 ,t 2 ,...,t m} is a collection of vertices, representing the process
[0036] tasks, E is a set of directed edges, representing dependencies between tasks.
[0037] cor(t i ,t j ): Any two tasks t in this layer of tasksi and t j correlation between.
[0038] c(t i ): Indicates task t i A collection of subtasks.
[0039] |c(t i )|: Indicates task t i The number of subtasks.
[0040] C i : The i-th cluster of a certain level in the flowchart.
[0041] needNum(C i ): for each cluster C i The number of tasks to fill.
[0042] leftTaskTime: The average runn...
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