Quantum-behaved particle swarm optimization (QPSO) algorithm based multi-objective dynamic workflow scheduling method
A quantum particle swarm and optimization algorithm technology, applied in the field of cloud computing, can solve the problem of few adjustment parameters
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[0033] The technical solutions provided by the present invention will be described in detail below in conjunction with specific examples. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention.
[0034] This implementation case dynamically divides the cloud computing workflow, and then uses the quantum particle swarm optimization algorithm to allocate the current optimal resources for the workflow tasks, thereby optimizing the execution time, cost and reliability of the workflow.
[0035] Such as figure 1 As shown, the method provided by the invention comprises the following steps:
[0036] Step 10, input the workflow V={v submitted by the user 1 ,v 2 ,v 3 ,v 4 ,v 5 ,v 6 ,v 7 ,v 8 ,v 9 ,v 10 ,v 11 ,v 12} and the user's QoS request {1h, 100﹩, 98%}. The workflow of this embodiment includes 12 tasks, and the input workflow is as follows figure...
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